Data & Applied Scientist Resume Samples

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DL
D Lindgren
Deron
Lindgren
33274 Boehm Highway
Detroit
MI
+1 (555) 466 5405
33274 Boehm Highway
Detroit
MI
Phone
p +1 (555) 466 5405
Experience Experience
New York, NY
Data & Applied Scientist
New York, NY
Maggio-Spinka
New York, NY
Data & Applied Scientist
  • Leading the application of machine learning and predictive modeling techniques with partners to solve business problems
  • Working with internal partners to cross-leverage, as well as develop and share new solutions specific to Ads domain
  • Working with the Product team to prototype, develop and refine data-driven product metrics and features
  • Driving creation of content in OSS and Microsoft big data technologies in support of developer events and architecture design sessions
  • Working closely with Microsoft Data Group engineering teams to influence the future product roadmap
  • Predictive data analysis oriented towards player behavior
  • 3) Run operational processes, including: monitoring data SLA levels, daily/weekly/monthly reporting processes, validating scorecard data. Operational processes are a key part of our LiveSite
Detroit, MI
Senior Data & Applied Scientist
Detroit, MI
Graham Inc
Detroit, MI
Senior Data & Applied Scientist
  • Applying machine learning and predictive modeling techniques with partners to solve business problems
  • Helping to govern and manage the enormous and complex pipeline of data that we use in our product and decision making
  • Direct prototyping and services work with customers and the Customer Solutions team manipulating data and helping develop methodologies to model and predict business outcomes
  • Partner with Program Management to identify and explore opportunities for the application of machine learning and predictive analysis
  • Senior candidates will be developing and driving new ways of thinking across groups within the division to improve quality, engineering productivity, and responsiveness to feedback and changing priorities
  • Working closely with Microsoft data product teams to influence the future product roadmap
  • Providing machine learning subject matter expertise and leadership to Microsoft teams worldwide
present
Philadelphia, PA
Principal Data & Applied Scientist
Philadelphia, PA
Feil, Kuhlman and Lehner
present
Philadelphia, PA
Principal Data & Applied Scientist
present
  • Working closely with Microsoft teams to influence the future product roadmap
  • Providing subject matter expertise and leadership to Microsoft teams worldwide
  • Drive improvements to the product design and architecture, leading to increased customer satisfaction
  • Apply machine learning and predictive modeling techniques across the business
  • Employ machine learning to detect and correlate problems
  • Learn how to build and sustain engagement from all levels of an organization
  • Educate and train others on modern applications of data science techniques
Education Education
Bachelor’s Degree in Computer Science
Bachelor’s Degree in Computer Science
University of Tennessee
Bachelor’s Degree in Computer Science
Skills Skills
  • Proficiency with at least one language for data analysis, such as R, Python, or Julia. Excellent SQL
  • Excellent written and oral communication skills, particularly the ability to synthesize complex problems/scenarios into easy-to-understand concepts
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
  • Detail-oriented, results-driven, with strong cross-group collaboration and communication skills
  • Hands-on approach to data analysis and a strong focus on quality
  • Excellent written and oral communication skills, particularly the ability to synthesize complex issues/scenarios into easy-to-understand concepts
  • Use data mining, modeling, and statistical techniques to create new, scalable solutions to enable both business and end-user scenarios
  • Comfortable with ambiguity and the ability to drive meaningful priorities and results out of the ambiguity
  • Strong SQL skills to handle large data sets
  • Effectively plan, contract and communicate with customers, partners, and co-workers to define deliverables, timelines, and responsibilities
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7 Data & Applied Scientist resume templates

1

Senior Data & Applied Scientist Resume Examples & Samples

  • Implement algorithms/models that scale and meet performance metrics
  • Deploy these models at operational scale using best of breed engineering practices in our applications and services
  • Partner with MSR and other product teams to develop new algorithms and techniques to solve new problems and obtain better model performance
  • Partner with Program Management to identify and explore opportunities for the application of machine learning and predictive analysis
  • Ingest, transform, and manipulate massive datasets in SQL or equivalent ETL tools
  • Develop reports, presentations, and dashboards to support internal partners
2

Data & Applied Scientist Resume Examples & Samples

  • Coming up with new techniques to detect for policy compliance, as well as leveraging state of the art methods for bad intent detection that will work at scale – with low latency and efficient compute
  • Working with internal partners to cross-leverage, as well as develop and share new solutions specific to Ads domain
  • Bachelor’s degree in Computer Science or a related field
  • 5-8 years work experience with large scale data mining/machine learning
  • Master’s or PhD in Computer Science
  • Experience in distributed systems, big data compute is strongly preferred
  • Demonstrated experience shipping high quality services
3

Data & Applied Scientist Resume Examples & Samples

  • Prior analytic consulting experience with stakeholders. Must have experience across several relevant business domains in the utilization of critical thinking skills to conceptualize complex business problems and their solutions using advanced analytics using large scale real-world business data sets; and
  • Independently run analytic projects and help our stakeholders to understand the findings and translate them into action to drive their business
  • Collaborate with others, apply critical thinking skills, and drive analytic projects end-to-end
  • Superior communication skills, both verbal and written; and
  • Strong SQL skills to handle large data sets
  • Advanced Statistical/Econometric software packages: R, Python, Matlab, & SAS; and
  • Data exploration, visualization, and management: Power BI, Excel
  • 7+ years of related experience required
  • Master’s degree required in statistics, mathematics, computer science or economics
4

Senior Data & Applied Scientist Resume Examples & Samples

  • Collaborating with Services business stakeholders, data science staff and data engineers to provide analytical, statistical modeling breakthroughs on key services programs and expand Nature Language Processing model and platform
  • Collecting requirements & performing hands on quantitative business analysis accessing multiple large databases
  • Performing hands on analysis with large unstructured or semi-structured data set to improve the performance of incidents classification models and platform
  • Hands on creation, presentation, scoring and deployment of behavioral and predictive models, using a variety of statistical procedures and best-in-class analytics practices
  • Performing data mining, forecasting, segmentation analysis using available software toolset
  • Performing ad-hoc analysis
  • Working with Data Sciences and BI staff to create, maintain, and update customer models
  • Helping develop business insights and provide consultative advices to stakeholders
  • Proficiency in data mining tools like R, SAS, AzureML, C#, Python
  • Excellent analytical and problem solving skills. Hands on experiences with Propensity Modeling, Forecasting, A/B testing, Clustering, Simulation, are required
  • Proficiency in data mining and text mining toolkits in R, NLTK, scikit-learn
  • Proficiency in handling unstructured and semi-structured data
  • Proficiency in SQL and relational databases and hands on experience working with large datasets
  • Knowledge of REST API and Azure development
  • 5+ years of experience in modeling and statistical analysis role
  • 3+ years of experiences in hands on Machine Learning development role
  • Excellent oral and written communication skills and collaborative skills
  • Strong client services orientation and consultative skills
  • Project management experiences
  • A PhD in Computer Science or related discipline is preferable, but an Advanced degree in Statistics, Operation Research, Computer Science or related field of study or equivalent experience combined with strong analytical background in problems relating to Big Data and Analytics is also acceptable
  • Experience with customer services and enterprise services is a big plus
  • Experience SCOPE and COSMOS, HADOOP is highly preferred
  • Experience with Azure Data Factory, Azure Data Lake, Redis, Azure EventHub is a big plus
  • Experience with open source search engine like ElasticSearch or Solr is highly preferred
5

Data & Applied Scientist Resume Examples & Samples

  • Extensive knowledge and experience in at least one of the following areas: data mining, web mining, statistics, business intelligence/customer intelligence, user modeling, information retrieval, databases, data warehousing, OLAP, data processing (ETL), e-metrics/measurement, parallel and distributed computation (two or more areas are preferred)
  • Extensive knowledge of COSMOS and PowerBI is a huge plus
  • Extensive data analysis/processing experience (minimum 5 years, preferred 7 years). Experience on web domain is a plus
  • Desire and eagerness to help improve the end-to-end Intune service experience for our customers
  • Strong prioritization, time management and organizational skills
  • Strong verbal and written communication skills with excellent interpersonal communication and collaboration skills
6

Data & Applied Scientist Resume Examples & Samples

  • Use data mining, modeling, and statistical techniques to create new, scalable solutions to enable both business and end-user scenarios
  • Predictive data analysis oriented towards player behavior
  • Deliver progression modeling, balance analysis, multiplayer performance and social impact analysis
  • Provide regular, timely reporting and performance monitoring to studio teams and key business stakeholders
  • Establish scalable, efficient, automated models for large scale data analyses
  • BA, BS degree in Computer Science, or equivalent experience. Masters or PHD strongly preferred
  • Passion for games, the game community and game design
  • Excellent analytical and problem solving skills, with hands-on experience applying it to big data
7

Principal Data & Applied Scientist Resume Examples & Samples

  • Bachelor’s or Master’s degree in a quantitative field, PhD preferred
  • 5 or more years’ experience using data to impact critical product or business decisions
  • An understanding that getting value from imperfect data and systems is a core virtue for a data scientist
8

Data & Applied Scientist Resume Examples & Samples

  • 2) Demonstrating technical acumen to understand the e2e flow or our data: from source system, to SQL DB to our UI data. Understand how and why the data is merged for users in UI views and reports. Though most of the role is operational in nature, candidates with a strong technical bend will have an edge
  • 3) Run operational processes, including: monitoring data SLA levels, daily/weekly/monthly reporting processes, validating scorecard data. Operational processes are a key part of our LiveSite
  • 2+ years of running business+technology solutions
9

Senior Data & Applied Scientist Resume Examples & Samples

  • Collaborate with various innovators across the company to further insights from across user/customer feedback, telemetry, and other related business data
  • Generate cross customer / product insights through collecting, parsing, managing, analyzing and visualizing large sets of data with a high level of autonomy
  • Building data manipulation, processing, and visualization tools and sharing these tools and your knowledge across the team, your partners, and Microsoft
  • Perform exploratory and targeted data analyses with diverse data sources that are not always “clean” (from messy/incomplete telemetry to survey results)
  • Identify and lead opportunities to improve the internal feedback analytics platform (e.g., useful transformations, identifying useful data sources, data viz)
  • Act as a thought leader for the use of data and analytics to drive critical business decisions, business strategy and product management activities; and ability to serve as coach / mentor for aspiring data scientists
  • Working knowledge of statistics, programming, machine learning, predictive modeling, and strong exploratory analysis skills
  • Bachelor’s degree in quantitative field (typically computer science, mathematics, engineering, physics, econometrics, operations research, or applied statistics). Master’s degree in Statistics, Business Analytics or an advanced computer programming field preferred
  • Experience with integrated Big Data programming environments and competency in major analytics/data mining software packages and programming languages/environments (e.g. Hadoop / Map-Reduce, COSMOS, Mahout; Python, C#, R, Spark, Matlab, SAS, SQL, etc.). SQL experience + R mastery required
  • Extensive hands on experience working with very large data sets, including statistical analyses, data visualization, data mining, and data cleansing / transformation
  • Strong ability to communicate deep analytical results in forms that resonate with scientific and/or business collaborators, highlighting actionable insights and improvement opportunities
  • Strong business acumen spanning a variety of disciplines or industries
10

Senior Data & Applied Scientist Resume Examples & Samples

  • A minimum of 7+ years of relevant work experience
  • Experience working with unstructured data and a solid understanding of BI and data solutions
  • Prior knowledge of data modeling and processing techniques for big data systems
  • Expert in querying and analyzing data using Scope, Hive, SQL, Python, R, and/or C#
  • Ability to articulate vision, requirements, and benefits to business and engineering partners
  • A MS degree (PhD preferred) in a quantitative discipline (Statistics, Mathematics, or Computer Science)
11

Data & Applied Scientist Resume Examples & Samples

  • PowerBI power-user. Familiar with the PowerBI toolset, and have applied to toolset for a business implementation
  • BS in Analytics, Statistics, Industrial Engineering or Supply Chain
  • 5+ years of building business+technology solutions
  • Demonstrated ability to influence and drive change across technology and business teams
12

Senior Data & Applied Scientist Resume Examples & Samples

  • PhD in Computer Science with focus on Robotics (or associated areas) preferred
  • Hands-on experience with state estimation, visual odometry, IMU sensor fusion, and simultaneous localization and mapping (SLAM)
  • Experience with distributed agents is a plus
13

Data & Applied Scientist Resume Examples & Samples

  • Advanced degree in Computational Linguistics, Linguistics or equivalent in related technical experience
  • Detail-oriented, results-driven, with strong cross-group collaboration and communication skills
  • Creativity, customer focus, and passion for quality
  • Minimum one year experience in quality assurance or experimental design for language/computational linguistics projects
  • Minimum one year experience in two of the following
  • Knowledge of Hadoop, or other big data systems
  • Proficiency in a language other than English
  • Experience developing or evaluating commercial or high-quality research software
14

Data & Applied Scientist Resume Examples & Samples

  • Analyze key performance indicators and communicate insights to the team to inform decisions
  • Build out our pipeline and insights for Minecraft: Education Edition
  • Collaborate with production, engineering and business teams to help make the right product decisions
  • Help empower every Minecraft team member to deeply understand player behavior, and turn that understanding into actionable insights with measurable improvements to the franchise
  • Help promote a data-driven and experimental culture across the organization, including more self-service tools for the team
  • 5 years of machine learning, business intelligence, and quantitative analysis experience, ideally in gaming and/or global-scale services
  • Practical experience optimizing data pipelines, and building data products using petabyte-scale data sets in Hadoop-based architectures
  • Experience with some or all of the following languages: SQL, R, Python
  • Track record of strong collaboration across disciplines such as marketing, engineering, and business
  • Excellent verbal, visual and written communication skills
  • Passion for gaming and entertainment
  • MS in Statistics, Computer Science, related field, or equivalent experience
15

Data & Applied Scientist Resume Examples & Samples

  • Design, prototype, implement and test machine learning and predictive analytics models
  • Partner with MSR to develop new algorithms and techniques to solve new problems and obtain better model performance
  • Partner with teams to identify and explore opportunities for the application of machine learning and predictive analysis
  • Provide machine learning and analytical leadership to internal partners
16

Data & Applied Scientist Resume Examples & Samples

  • 3+ years of experience with R and Python
  • 2+ years of experience with Microsoft Azure and experience deploying models to Azure ML
  • 3+ years of experience building and implementing some of the following algorithms: time series, regression, classification, clustering, curve fitting, decision trees, neural networks, support vector machine, and ensemble methods such as Random Forests
  • 2+ years of building recommendations engine and tuning/enhancing them
  • 3+ years of experience with data manipulation using Microsoft SQL stack, PowerBI, or similar SQL stack
  • 2+ years of experience with Hadoop or other big data tools
  • Experience with Java or C#
  • Creative and self-motivated data scientist with excellent design, implementation and communication skills
17

Senior Data & Applied Scientist Resume Examples & Samples

  • Strong software development skills in C# and ability to produce maintainable and reusable code
  • Experience in large scale data processing, machine learning and/or natural language processing
  • Native English speaking is preferred not required
18

Data & Applied Scientist Resume Examples & Samples

  • Generate cross customer / product insights through collecting, parsing, managing, analyzing and visualizing large sets of data with some autonomy
  • Develop and deploy modern machine learning and statistical methods for finding structure in large data sets (classification, predictive modelling, etc.)
  • Identify and lead opportunities to improve the internal feedback platform (e.g., useful transformations, identifying useful data sources, data viz)
  • Discovers “stories” told by the data and presents them to leadership, program managers and engineering
  • Participate in the Data Science and Machine Learning Community within the company to contribute and adopt useful practices
  • Experience in machine learning and/or combining R with interactive data visualizations
  • Bachelor’s degree in quantitative field (typically computer science, mathematics, engineering, physics, econometrics, political science, operations research, or applied statistics). Master’s degree in Statistics, Business Analytics or an advanced computer programming field preferred
  • Experience in major analytics/data mining software packages and programming languages/environments (e.g. Hadoop / Map-Reduce, COSMOS, Mahout; Python, C#, R, Spark, Matlab, SAS, SQL)
  • Hands on experience working with large data sets, including statistical analyses, data visualization, data mining, and data cleansing / transformation
  • Ability to communicate deep analytical results in forms that resonate with scientific and/or business collaborators, highlighting actionable insights and improvement opportunities
  • Natural Language Processing experience a plus
19

Senior Data & Applied Scientist Resume Examples & Samples

  • 80% of the time driving multiple analytic projects with high complexity, strategic value, and executive visibility. Candidate must be available to travel an average of one week/month
  • 20% of the time sharing best practices and growing the culture of data driven decision making in Microsoft
  • Must have experience across several relevant business domains/industries in the utilization of critical thinking skills to conceptualize complex business problems and their solutions using advanced analytics with large scale real-world business data sets
  • The candidate must be able to independently run analytic projects and help our clients understand the findings and translate them into action to benefit their business
  • Work independently or manage a virtual project team that will research innovative solutions to challenging business problems
  • Visualization of analytic results in a form that is consumable by a diverse set of stakeholders
  • 5+ years of related experience required
  • Masters or doctorate degree in computer science, statistics, mathematics, economics, or other quantitative-focused field (within six months of graduation). Ph. D in quantitative field desirable
  • Proficiency in SQL, R or Python
20

Principal Data & Applied Scientist Resume Examples & Samples

  • Experience in Recommendation Systems and Personalization
  • Experience in targeting algorithms
  • Experience in Search, Information Retrieval, Natural Language Processing, Knowledge Graphs, Semantic Web
  • Experience in optimization algorithms and numerical computation
  • Experience with other large-scale data frameworks such as Cosmos
  • Experience with cloud computing platforms and large web-scale distributed systems
21

Data & Applied Scientist Resume Examples & Samples

  • Reframes specific questions to provide valuable context, and frames broad or ambiguous questions into discrete, manageable problems with well-defined, measurable objectives
  • Identifies data sources, integrates multiple sources or types of data, and applies expertise within a data source in order to develop methods to compensate for limitations and extend the applicability of the data
  • Minimum of 5 years of relevant work experience in Advanced analytics using machine learning and statistics
  • Proven ability to provide hands-on practical use of science of data and analytics
  • Strong background in Machine Learning - Time series, unsupervised classification, decision tree, logistic and multiple regression
  • Statistics - Parametric, Non-parametric tests, Multivariate, PCA, Factor analysis
  • Experience working with unstructured and structured data with a solid understanding of Big data solutions
  • Expert in querying and analyzing data using R, Python, SAS, SPSS, Scope, SQL, Scope
  • Effective communication skills and the ability to work collaboratively with stakeholders, executives and subject matter experts
  • A MS degree (or a PhD) in a quantitative discipline (Computer Science, Statistics, Mathematics, Physics, Operation Research)
22

Data & Applied Scientist Resume Examples & Samples

  • Being the key architect for all customer focused data science initiatives and investigations in the Azure Storage team
  • Proactively defining, measuring, analyzing, researching, and driving improvements in the Storage business
  • Applying statistical concepts and techniques to analyze business metrics, engineering data, customer consumption patterns, and more
  • Analyzing petabytes of complex data from diverse sources using a variety of tools and data analysis techniques
  • Working with Finance, BizDev, Marketing and other partner teams to enhance the data modeling as well as help them to unlock additional value for Azure
  • Presenting findings of research to leaders and stakeholders to influence Storage team strategy and execution
  • Applying the lessons from the customer analytics framework by working closely with a number of key customers and partners (every member of the team has customer focus and ownership as a key deliverable)
  • Expert in one or more statistical analysis tools such as R, SAS, SPSS
  • Expert in querying and analyzing data using Scope, Hive, SQL, Python, R, and/or C# including the skills necessary to develop metrics, create reports, and interpret analytical results
  • Ability to prototype statistical analysis and modeling algorithms, and apply these algorithms for data driven solutions to problems in new domains
  • Ability to collaborate with partners and drive analytic projects end-to-end
  • Attention to detail and data accuracy
  • Strong interpersonal, communication and presentation skills
  • Solid understanding of BI and data solutions, including Power-pivots, cubes, data warehouse, and DataMart's
  • Experience in a Data Scientist role
  • 5+ years experience as a Data Scientist
23

Data & Applied Scientist Resume Examples & Samples

  • Develop code to scale machine learning models within a MapReduce framework containing some of the largest datasets in the world
  • Generate actionable insights to improve the Bing Ads search advertising platform through sales, marketing and product improvements
  • High competency with database systems required, experience with unstructured data and/or streams preferred. Experience with SQL, Pig, Hive or similar required. Experience writing custom MapReduce code (reducers, combiners etc.) strongly preferred
  • Expertise with statistical modeling with R, Matlab, Octave, Python or similar strongly preferred
  • Great communications skills, both verbal and written - especially as it pertains to communicating complicated technical concepts to non-technical stakeholders
  • Ability to juggle multiple projects with high level of ambiguity and shifting priorities in a fast-paced environment
  • 2+ years Industry experience and a Master’s Degree in Math, Computer Science, Economics, Industrial Engineering, Machine Learning or a related field (or the equivalent combination of education and experience). Doctorate/PhD preferred
  • Extensive knowledge and experience in the following areas: machine learning, statistical modeling, data analysis, simulation, MapReduce
  • Preferred: Experience analyzing large scale data related to online businesses, online-advertising and/or e-commerce data
  • Preferred: knowledge of and some experience with recommender systems
24

Data & Applied Scientist Resume Examples & Samples

  • Support execution and operational improvements of the Azure BG
  • Enable automation to eliminate manual process
  • Help drive insights into engineering and other parts of the Azure business
  • Define and implement effective key performance indicators (KPIs) and other measurements to ensure business impact
  • Gather and analyze qualitative and quantitative data to identify meaningful actions
  • Design and drive implementation of reporting by interfacing with business, engineering, finance, operations, and systems teams to provide actionable insights
  • Deliver on ambiguous projects with multiple stakeholders, unclear requirements and incomplete data
  • Prior exposure to big data/ML systems
  • Proven excellent analytical skills
  • Proven strong collaboration and project management skills for effective internal and external relationships and making change happen
  • Demonstrated technical curiosity and aptitude to quickly master service capabilities, technical issues, business trends, and customer needs
  • Bachelor’s Degree in computer science or related discipline, or equivalent experience
  • Prior experience with a major cloud platform (Azure, AWS etc.) is desired but not required
  • Prior experience in Enterprise services including SAP, MSSales, GSX is desired but not required
25

Senior Data & Applied Scientist Resume Examples & Samples

  • 2+ years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive forecasts, and/or optimization models
  • Expert in analysis of very large datasets; strong proficiency in R, SQL, Azure ML
  • Also prefer skills and experience with Spark, Hive, Pig, SAS macros and familiarity with building web services in Azure
  • Skilled at all stages of the development lifecycle including defining key business questions, recommending measures, managing data sources, dataset creation, implementing machine learning (supervised and unsupervised), predictive modeling, statistical analysis, model scoring, and applying the model to new and existing IT services
  • Self-driven with ability to prioritize assignments, and work collaboratively with key stakeholders and subject matter experts within a matrix team environment
  • A great attitude
26

Senior Data & Applied Scientist Resume Examples & Samples

  • Help improve the way we gather and prepare data for analysis, driving critical business decisions through insights and KPIs that matter most across a variety of problem domains
  • Employ machine learning to detect and correlate problems
  • Build models, simulations, and scalable and automated analytical systems
  • Lead and collaborate with experts from across the company to advance data science and data engineering best practices
27

Data & Applied Scientist Resume Examples & Samples

  • Work directly with Xbox teams to develop analytical best practices for measurement and design of games
  • Establish core measurements and methods that can be used across multiple games, game services, and HW
  • Working knowledge of one or more of the following: R, Matlab, JMP, or equivalent statistical modeling, DW, Hive, and SQL
  • BA, BS degree in Computer Science, or equivalent experience
  • Masters or PHD strongly preferred
28

Data & Applied Scientist Mgr Resume Examples & Samples

  • You will own the fiber optic network traffic demand forecasting for all cloud services and have hands-on responsibility of providing global demand forecasts on a regular basis
  • Your forecasts will drive major decisions such as short and medium term capacity planning and long term major asset acquisition. Your team’s responsibility will include performing analyses on data to identify traffic trends, patterns, correlations, and providing insights from data to stakeholders
  • You will be collaborating closely with Network Engineering, Product Managers, Operations Managers, Capacity Planning, and Finance to drive forecasting. You will be responsible for managing the relationship with stakeholders, collecting their requirements, planning and managing to deliver to their needs. It will be essential for you to develop a deep understanding of your partners? problems and challenges, provide insights to guide their decisions, and communicate effectively
  • You are expected to bring extensive, proven experience in data networks, how they operate, how different events (e.g. new service offerings, feature changes, engineering changes, datacenter activities) impact the network traffic. You will be faced with problems ambiguous in nature and will need to think creatively and practically to develop effective methods and solutions to address them
  • You will need to develop a solid grasp of technical and operational intricacies of our cloud network, stay attuned to operational changes in the network, datacenters, and service offerings, understand their impact on demand, develop and implement credible methods to reflect those changes in forecasts
  • Solid operational and technical understanding of enterprise data networks (is a must.) Strong conceptual, analytical, and problem-solving abilities
  • Ability to conduct statistical analysis and develop analytical modeling
  • Ability to bring quantitative data and qualitative business scenarios together to develop credible forecasts and decision support models
  • Individual must be self-directed with a relentless drive to improve demand forecasting accuracy and passion for developing deeper insights for Microsoft’s cloud services and its cloud network
  • Excellent creative and practical thinking skills to solve complex problems with ambiguities and no obvious solutions
  • Demonstrated experience in managing people and managing complex projects, demand forecasting, planning, and problem solving
  • Master’s degree in engineering or science, preferably in Electrical Engineering, Electronics Engineering or Computer Science
  • 10+ years of work industry experience, and 5+ years of hands-on experience in enterprise data networks
29

Data Applied Scientist Resume Examples & Samples

  • Applicants should have Master or PhD degrees in Computer Science, Information Science, Statistics, or related technical fields
  • A master degree holder is required to have 3+ years of working experience in a Machine Learning or Data Science job
  • Expertise on managing and processing time series data is a plus
30

Data & Applied Scientist Resume Examples & Samples

  • Become a subject matter expert in the C+E business and BI ecosystem
  • Collaborate with end users to understand objectives, identify analysis opportunities, and prioritize projects in order to deliver maximum business impact
  • Manage the timely delivery and accuracy of C+E RoB artifacts and coordination with stakeholders across the organization. Recognize opportunities for process improvements and drive standardization and repeatability
  • Support development and management of metrics, KPIs, and dashboards
  • Identify changes in customer behavior, system performance, or financial results, and deliver the necessary insights to explain them
  • Define, develop, and evangelize self-serve reports that meet the needs of disparate audiences across the organization and Microsoft
  • Educate customers on how to leverage data as an asset for their function/business
  • Ensure the ongoing documentation of analysis methodologies and their results
  • Demonstrated project management skills (PMI certification a plus) o Demonstrated analytical ability, particularly related to complex problems and concepts
  • Proficient with T-SQL and Excel. Familiarity with Cosmos/Scope is a plus
  • 7 years of experience in Program Management, Analytics, BI, or data driven business strategy
  • Experience analyzing and streamlining complex business processes (PMP, Six Sigma qualifications preferred)
  • Bachelors degree in Computer Science, Engineering, Business, Statistics or closely related field
  • Effective presentation skills and experience with audiences of all levels
  • Demonstrated ability in prioritizing multiple work streams and coordination across numerous stakeholders
  • Self-discipline and a drive for results
  • Comfortable with ambiguity and the ability to drive meaningful priorities and results out of the ambiguity
31

Data & Applied Scientist Resume Examples & Samples

  • 2 years of experience with machine learning, natural language processing and experiment design
  • Experience applying statistical methods such as hypothesis testing, p-values, confidence intervals, regression, classification, and optimization
  • Development experience in C#/C++/Java/R/Python or similar programming language
  • Strong communications skills written research results and effective presentations
  • Familiarity with distributed data processing/analysis and modeling paradigms, such as Map-Reduce, is a plus Expertise in survey methodology is a plus
  • BS/BA in computer science, Engineering, machine learning, statistics or equivalent related field (PhD preferred)
32

Senior Data & Applied Scientist Resume Examples & Samples

  • 3-5+ years (including MS program or PhD program) of experience working with large data sets or doing large scale quantitative analysis
  • Bachelor’s or Master’s degree, or PhD degree in Computer Science, Mathematics, Engineering, Statistics or other related technical major fields
  • 2+ yearns processing large data sets through statistical software (ex. R, SAS) and program language (ex, Python), or other methods. Strong algorithmic problem-solving skills
  • 2+ years of fundamental understanding of statistics, hypothesis testing, p-values, confidence intervals, regression, classification, and optimization is a core requirement
  • 2+ years with one or more of the commercial or open source statistical and various machine learning software
  • 2+ years working with Hadoop, Pig/Hive, Spark, MapReduce; Familiarity with Cosmos (via Scope/Spark) is a plus
  • Effective presentation skills and experience in good communications with audiences of all levels
  • Demonstrated ability in prioritizing multiple work streams and coordination across numerous stakeholders Creative and innovative thinker
  • Strong communication and collaborative skills
  • Preference towards to the abilities of having good general coding skills, good computation skills and software development experience (via Python, C/C#, SQL)
33

Data & Applied Scientist Resume Examples & Samples

  • Understanding of the e2e picture of the MSC ecosystem inclusive of Lifecycle Management, Demand Planning, Supply Planning, and Logistics/Fulfillment mechanisms and make actionable recommendations on design, and data flow
  • Ability to own at least one supply chain area e2e: from an understanding of the source data, to understanding the ETL and aggregations, to understanding the business needs
  • Drive BI visualization standards: passionate about polish, and understand which visuals drive home the intended message
  • Ability to partner directly with the MSC GMs and Directors to understand business problems and drive recommendations back into IT solution providers and other stakeholders
  • Foster a data-driven culture within MSC by using analytics & data through partnerships, thought leadership, solutions, consultation, and training while educating clients on how to leverage data to tell stories and how to use self-service solutions
  • Integrate across the different geographies and organizations to proactively manage business objectives
  • Propose data driven solutions to proactively manage MSC strategic agenda
  • Effectively plan, contract and communicate with customers, partners, and co-workers to define deliverables, timelines, and responsibilities
  • 7+ years of building business + technology solutions
  • BA/BS required, Advanced degrees preferred. Preferably in Analytics, Statistics, Industrial Engineering, Supply Chain or Business Administration / Finance
  • 5+ years’ experience in supply chain processes, flows and data architectures
  • Relevant progressive work experience in this domain applying analytical methods to business problems, driving improved decision-making and outcomes; BI experience preferred
  • PowerBI power-user
  • Familiar with the PowerBI toolset, and have applied to toolset for a business implementation
  • Excellent verbal and written communication skills and the ability to interact professionally face to face or virtually with a diverse group of executives, managers, and subject matter experts
  • Apply a breadth of tools, data sources, and analytical techniques to answer a wide range of high-impact people-related business questions
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Senior Data & Applied Scientist Resume Examples & Samples

  • Applying machine learning and predictive modeling techniques with partners to solve business problems
  • Developing commercially viable analytics solutions using OSS, Windows, Azure, Bing, and Office technologies
  • Technical subject matter expertise in OSS and Microsoft big data technologies to develop technical content in support of developer events, architecture design sessions, and resolve issues
  • 5+ years of machine learning, business intelligence and quantitative analysis experience
  • At least 3 years industry experience with machine learning algorithms for classification, regression, clustering, reinforcement learning or dimensionality reduction with expertise one or more application domains of NLP, image processing, time series analysis
  • At least 3 years experience with R and/or Python, experience with Scikit-learn a plus
  • Comfortable with at least one general purpose programming language (C, C#, C++, Javascript) and SQL
  • Experience working with application development practices and version control systems
  • Experience with one or more of the DNN frameworks, including CNTK, MXNet, TensorFlow, Caffe
  • Experience with Hadoop/Spark
  • Great communication and presentation skills
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Data & Applied Scientist Resume Examples & Samples

  • Establish core measurements and methods that can be used across multiple games, game services, and hardware
  • Recommend new architectural designs and enhancements to existing data systems in order to optimize for high speed, low latency reporting and self-service analytics for stakeholder clients
  • 5+ years of data science and/or business intelligence experience
  • 2+ years of experience with R or Python scripting (or other platform-agnostic language)
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Senior Data & Applied Scientist Resume Examples & Samples

  • Graduate work in Statistics, Computer Science, Physics, Bioengineering, Biostatistics Economics or related discipline. PhD preferred
  • Demonstrated history of experience in large scale, distributed computing
  • Research background in statistics, analytics, and machine learning, minimum of 2 years using SQL, R, Python tools
  • Experience in C#/Java/C++/ OR C – minimum 6 months
  • Some training in health-related field: medicine, nursing, medic, is a plus. Otherwise strong interest in making an impact in the health industry
  • Strong curiosity and self-starting approach to challenging problems
  • Communicates well with technical and non-technical colleagues and partners, and contributing modeling expertise as a team player
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Data & Applied Scientist Resume Examples & Samples

  • End-to-end execution of the data science process, from understanding business requirements, data discovery and extraction, model development and evaluation, to production pipeline implementation
  • Develop and deploy solutions with Microsoft Partners for solving business problems using machine learning and predictive modeling techniques
  • The ability and effectiveness of working in a significant technical problem domain, in the terms of plan, design, execution, continuous release and service operation
  • Software engineering fundamentals, including coding, problem solving and data analysis skills
  • Customer/end result/metrics driven in design and development
  • The ability to self-teach in new domains
  • MS or PhD in Computer Science, Economics, Statistics, Operations Research or other technical field
  • 5+ years of real-world experience with machine learning algorithms for classification, regression, clustering, reinforcement learning or dimensionality reduction with expertise in time series analysis
  • Skilled in R and/or Python, experience with Pandas a plus
  • Experience with Cosmos/Hadoop/Spark
  • Experience with application development practices and version control systems
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Data & Applied Scientist Resume Examples & Samples

  • Help our efforts to improve the way we gather and prepare data for analysis to help make critical business decisions and the KPI’s that matter most across a diversity of problem domains
  • Design and develop new tools and processes to enable better data modeling, analysis, and experimentation
  • Drive improvements to the product design and architecture, leading to increased customer satisfaction
  • Lead and collaborate with experts from across the company including Microsoft Research to advance data science best practices
  • Programming skills (esp. related to data technologies like C#, Java, Python, etc.)
  • An ability to formulate a business problem to an analytics/data science problem and drive the solution
  • Stats or data analysis experience working with advanced tools like R, SAS, SPSS, advanced Excel, preferred
  • 2 years of commercial software development experience
  • 1 year of experience in data analysis environment
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Data & Applied Scientist Resume Examples & Samples

  • Working closely with Microsoft Data Group engineering teams to influence the future product roadmap
  • 10+ years of real-world experience leading the application of machine learning algorithms for classification, regression, clustering, reinforcement learning or dimensionality reduction with expertise one or more application domains of NLP, image processing, time series analysis
  • Domain expertise in one or more of financial services, retail, marketing, health care, manufacturing
  • Skilled in at least one general purpose programming language (C, C#, C++, Javascript) and SQL
  • Skilled in one or more of the DNN frameworks, including CNTK, MXNet, TensorFlow, Caffe
  • Exceptional decision-making skills, conflict resolution, and follow through with ISV partners
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Data & Applied Scientist Resume Examples & Samples

  • Experienced professional or an active researcher in one or multiple of the following areas: OCR-ICR technologies, Artificial Intelligence, Semantic Technologies, Natural Language Processing, Image Mining, Pattern Recognition on Digital Media, and Information Retrieval (handling datatypes, ranging from traditional structured data, semi-structured data such as logs; text, social networks, audio, images, and video)
  • Learning Models: Convolutional, Recurrent Networks, regularization and optimization for training deep models. Deep Learning Research: Neural Language Models, esp. for the contexts of text disambiguation and categorization
  • Must have experience across several relevant business domains in the utilization of critical thinking skills to conceptualize complex business problems and their solutions using simulation modeling and advanced analytics using large scale real-world business data sets
  • Communication and Collaboration Skills
  • Collaborate with partners, apply critical thinking skills, and drive analytic projects end-to-end Superior communication skills, both verbal and written
  • Minimum 3+ years of technical experience
  • Ph. D. in quantitative field (Mathematics, Computer Science, Statistics, Economics, etc.) desirable
  • Prior consulting experience is a definite plus 85% of the time driving multiple analytic projects with high complexity, strategic value, and executive visibility
  • 15% of the time sharing best practices and growing the culture of data driven decision making in Microsoft Must be willing to do some travel
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Data & Applied Scientist Resume Examples & Samples

  • Direct services work with customers and the Customer Solutions team manipulating data and helping develop methodologies to model and predict business outcomes
  • Helping to develop the skills of the broader product and services team as data-savvy leaders who ask great questions and make informed decisions
  • 2+ years of professional data science experience or combination of work and postgraduate education in data science
  • Experience with agile development methodology
  • Experience and proficiency in coding skills relevant for data science, especially Python
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Senior Data & Applied Scientist Resume Examples & Samples

  • Direct prototyping and services work with customers and the Customer Solutions team manipulating data and helping develop methodologies to model and predict business outcomes
  • Working with the Product team to prototype, develop and refine data-driven product metrics and features
  • Helping to govern and manage the enormous and complex pipeline of data that we use in our product and decision making
  • 5+ years of professional data science experience or combination of work and postgraduate education in data science
  • Experience and proficiency in coding skills relevant for data science
  • Experience in NoSQL database (e.g. MongoDB) and Relational database (e.g., Oracle, SQLServer or PostgreSQL)
  • Excellent oral communication skills and be able to interact effectively with development, operations and business teams in Microsoft
  • Expertise in one or more computational social science disciplines
  • Experience with Hadoop/MapReduce or Spark
  • Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, gender, sexual orientation, gender identity or expression, religion, national origin, marital status, age, disability, veteran status, genetic information, or any other protected status
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Xbox Data & Applied Scientist Resume Examples & Samples

  • Work directly with Xbox teams to develop analytical best practices for measurement and design of platform features and games
  • Conduct predictive data analysis oriented towards player behavior
  • Collaborate with data modeling and visualization teams to incorporate best practices into sprint planning
  • 3+ years of data science and/or business intelligence experience
  • A Bachelor’s degree in Computer Science, Mathematics, Statistics, Machine Learning or related technical field
  • Ability to apply statistics, data mining and machine learning techniques to create new, scalable solutions for business problems
  • Creation and implementation of statistical predictive models including such algorithms as decision trees, regression, clustering, association, factor analytic techniques, etc
  • Advanced working knowledge of data mining using SQL, ETL and Data Warehouses. Need to be able to formulate complex SQL queries and have experience working with BI and visualization tools
  • A Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Machine Learning or related technical field
  • Excellent verbal, written and collaborative communication skills in a cross-team environment with the ability to translate complex information
  • PhD in Computer Science, Mathematics, Statistics, Finance, Machine Learning or related technical field
  • Experience with Azure tools and technologies (Hadoop, HDFS, Hive/Pig, Spark)
  • Ability to develop prototypes by compiling, manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
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Xbox Data & Applied Scientist Resume Examples & Samples

  • Conduct predictive data analysis oriented towards player behavior. Model player experiences using decision tree analysis and multivariate regression analysis
  • Establish scalable, efficient, automated models for large scale data analyses. Collaborate with data modeling and visualization teams to incorporate best practices into sprint planning
  • Excellent analytical and problem-solving skills, with hands-on experience applying it to big data
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Modeling Data Applied Scientist Resume Examples & Samples

  • B.S. in Computer Vision, Mathematics, or equivalent
  • Experience working with 2D and 3D geometry
  • 7+ years industry experience
  • Experience with Computer Vision, including Visual SLAM / Odometry
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Data & Applied Scientist Resume Examples & Samples

  • Become a subject matter expert in the C+E business and underlying data ecosystem
  • Identify changes in customer behavior, system performance, or financial results, and deliver the necessary insights to explain them and recommend actions to be taken
  • Ensure the ongoing documentation of analysis methodologies and results
  • Educate users about how to leverage data as an asset for their particular function
  • 3-6 years of experience in analytics, business intelligence, or data driven business strategy
  • Demonstrated analytical ability; problem deconstruction, statistical competency, meticulous forensic analysis skills, data validation, and scientific rigor
  • Highly proficient with T-SQL and Excel
  • Excellent written and oral communication skills, particularly the ability to synthesize complex problems/scenarios into easy-to-understand concepts
  • Effective presentation skills and experience with engaging audiences of all levels
  • Effective in rapidly evolving environments and working across organizational boundaries. Creative, innovative, organized thinker, with a high attention to detail
  • 5-10 years of experience in analytics, business intelligence, or data driven business strategy
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Data & Applied Scientist Resume Examples & Samples

  • Lead cross-team projects that deliver workflow automation solutions and aggregated data solutions that consume from the warehouse which enable business improvements
  • Collaborate with our business process owners to understand objectives which deliver maximum business impact and return on investment
  • Hand on design, build and deliver the data model and data process automation that transforms raw data into actionable information
  • Implement data processing and monitoring standards to address data quality
  • Ensure the automation solutions are stable, supportable and dependable
  • Bachelor’s degree in Computer Science, Engineering, related technical field or 3+ years of work experience in program/project management or data analytics
  • 3+ years of solid data analysis experience with one of more of the following: T-SQL, Analytics method, scripting, ETL, Modeling, Excel and applying Business Intelligence systems
  • Experience in leading projects that deliver workflow automation solutions and aggregated data solutions
  • Demonstrated ability to work through ambiguity and put forward creative, innovative solutions which maximize business impact
  • Skills in database design and multidimensional data modeling
  • Effective in communicating the approach & insights for complex issues/scenarios into easy-to-understand concepts
  • Background in data warehousing principles, architecture and its implementation to improve business processes
  • Sound understanding of object oriented concepts, UI best practices
  • Possess a strong work ethic, be self-sufficient, and comfortable working in a complex and fast paced environment
  • Ability to balance competing demands for resources and adapt to changing priorities