Data & Applied Scientist Job Description
Data & applied scientist
provides data modeling, mining, pattern analysis, data visualization and machine learning/deep learning solutions to address technical services, manufacturing and integrated supply chain needs.
Data & Applied Scientist Duties & Responsibilities
To write an effective data & applied scientist job description, begin by listing detailed duties, responsibilities and expectations. We have included data & applied scientist job description templates that you can modify and use.
Sample responsibilities for this position include:
Contribute to the technical content of proposals and technical products such as journal and conference publications and technical presentations will be expected
Use Python and other such tools to develop, test and validate supervised & unsupervised predictive machine learning algorithms
Be a mentor for other team members in all technical aspects while designing and developing statistical algorithms
Work under the technical guidance of senior staff
In depth knowledge of classification & clustering algorithms
Oversee the development of high-performance machine learning models to predict and classify clean and malicious activity
Provide technical leadership to your team by reviewing problem sets, proposing prediction models, and reviewing experiments and models
Act as a resident thought leader for machine learning, statistics, and experiment design
Prototype then deploy machine learning models that make our customers' lives easier
Application of standard theories, principles, methods, tools and technologies within specialty field
Data & Applied Scientist Qualifications
Qualifications for a job description may include education, certification, and experience.
Licensing or Certifications for Data & Applied Scientist
List any licenses or certifications required by the position: PMP, CAPM, CCA, MCSE, MCITP
Education for Data & Applied Scientist
Typically a job would require a certain level of education.
Employers hiring for the data & applied scientist job most commonly would prefer for their future employee to have a relevant degree such as Master's and Bachelor's Degree in Computer Science, Engineering, Machine Learning, Physics, Statistics, Applied Statistics, Intelligence, Mathematics, Technology, Economics
Skills for Data & Applied Scientist
Desired skills for data & applied scientist include:
Algorithms
Innovative methods
Technical
Her own analysis of scalability and applicability to the formulated problem
Operational metrics
Data mining using SQL
ETL and Data Warehouses
Cloud computing and online services business models
Machine learning
Applies his
Desired experience for data & applied scientist includes:
Software engineering skills shipping products or services for more than 7+ years using high level languages (C#, C++, Java, F#), data manipulation (SQL), scripting languages (Python, Perl), and common ML and analysis tools (R, SAS, SPSS, Mat Lab)
Prior analytic consulting experience with stakeholders
Work with a diverse set of data sources, such as time series data, spatial, graph data, semi-structured and unstructured data, and build statistical/machine-learning models in support of on-demand, real-time analytic services
Keep abreast of the latest developments in the field by continuous learning and proactively championing promising new methods relevant to current challenges
Collaborate closely with university partners, other scientists and engineers in a multi-disciplinary work environment
Strong knowledge and skills in rapid prototype programming languages, such as Python, Java, and/or R
Data & Applied Scientist Examples
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Data & Applied Scientist Job Description
Job Description Example
Our innovative and growing company is looking for a data & applied scientist. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for data & applied scientist
- Work closely with business leaders to understand the pain points and/or proactively identify opportunities and use statistical knowledge to solve those complex problems
- Leverage knowledge of R/SAS/Python, to design and develop best in class statistical models to provide data insights
- Gathers data from data warehouse and other systems to create models and provide recommendations
- Design rich visualizations to communicate complex ideas easily to business leaders
- Partner with end business users to understand their Data/BI needs and drive the solutions
- Proactively look out for data related issues/problems in business unit and suggest innovative solutions
- Apply and help institute best practices, methodology and standards in Data Analysis & its visualization
- Support enterprise data management strategies, guiding principles, processes and standards
- Create design and development specifications, and metadata documentation
- Assist with data quality research and user acceptance testing
Qualifications for data & applied scientist
- Ability and inclination to see ideas realized in practice
- Strong analytical, written and verbal communication skills, including the ability to explain and interpret the analytic models and outcomes in both research and application contexts
- Proficiency in publicly available data analytics toolkits (such as Scikit-Learn, Mallet)
- Deep Learning methods and tools
- Experience in manipulating and analyzing large data sets using existing Big Data technologies such as Hadoop and other high performance computing platforms
- Experience with R, Python, Azure ML, Cosmos, SQL is a plus
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Data & Applied Scientist Job Description
Job Description Example
Our growing company is searching for experienced candidates for the position of data & applied scientist. We appreciate you taking the time to review the list of qualifications and to apply for the position. If you don’t fill all of the qualifications, you may still be considered depending on your level of experience.
Responsibilities for data & applied scientist
- Collaborate with team members across CSS Technical Support Business Units (SBU’s) and Engineering teams to create and improve long range forecasts and increase business insight
- Perform statistical analysis to measure key support metrics, such as abandonment rate, first contact resolution or backlog, and make recommendations to the business on impacts to forecasting Manage and improve data systems and algorithms that drive run rate forecasts
- Provide technical leadership to the team on designing, prototyping, implementing and testing descriptive and predictive analytics models
- Partner with cross-functional teams to identify and explore opportunities for the application of machine learning and predictive analysis
- Drive department results
- Compiles and analyze data from different sources
- Manage medium to large project/process efforts with expanded scope
- Communicate across, up, and down the organization
- Seeks regular feedback from internal and external customers and peers on strategy, process, and system improvements to develop pro-active solutions to problems
- Identifies and resolves issues, escalating when necessary
Qualifications for data & applied scientist
- 10+ years of software development experience with OOP preferably C# / C++ optional
- A history of successful implementation and timely shipment of high quality products is required, preferably experience building scalable, secure, high-performance, multi-threaded server applications & services
- Excellent data modeling and coding skills
- Azure experience and a passion for gaming desired
- Bachelor’s degree in quantitative field (typically computer science, mathematics, engineering, physics, econometrics, operations research, or applied statistics)
- Experience with integrated Big Data programming environments and competency in major analytics/data mining software packages and programming languages/environments
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Data & Applied Scientist Job Description
Job Description Example
Our company is growing rapidly and is looking for a data & applied scientist. To join our growing team, please review the list of responsibilities and qualifications.
Responsibilities for data & applied scientist
- Identify improvements in reporting methodologies and standards
- Lead a strong team of data scientists and security researchers to deliver on the team’s reputation systems and next gen protection goals
- Monitor models' performance and ensure they continue to work well
- Provide easily digestible visualizations and explanations for what a model does and how well it performs
- Communicate results and performance to a wide range of disciplines
- Help shape vision, design, architecture and roadmap for the Data Science team to provide advanced predictive and prescriptive analytics to help the company drive customer success
- Drive collaboration and partnership with internal Customer Success teams on business and customer requirements and prioritization, centered on improving Customer Journey’s
- Partner closely with our legal teams to ensure we are treating all customer data to comply with appropriate confidentiality and usage
- Represent the data science team with internal/external partners and senior leadership
- Hire, retain and grow a team of highly skilled Data Scientists and Data Engineers
Qualifications for data & applied scientist
- Software engineering skill in high level languages (C#, C++, Java, F#), data manipulation (SQL, Cosmos, Hadoop), scripting languages (Python, Perl), and common ML and analysis tools (R, SAS, SPSS, MatLab)
- 4+ years experience in advanced analytics and machine learning model development and validation
- 2+ years experience working in industry, leading analytic-based projects, and delivering results within scope, funding, and duration
- 2+ years experience leading projects and interacting with non-technical users to explain modeling results and meaning
- Forecasting (ARIMA, ARCH, GARCH)
- Anomaly Detection
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Data & Applied Scientist Job Description
Job Description Example
Our company is looking for a data & applied scientist. Thank you in advance for taking a look at the list of responsibilities and qualifications. We look forward to reviewing your resume.
Responsibilities for data & applied scientist
- Champion the culture of data driven and growth hacking
- You have experience in (or are interested in learning) Python, R, SQL Clustering, classification, regression
- Sequence to sequence models Spark MLLib, scikit-learn TensorFlow, Keras
- Develop mathematical and/or stochastical model to link probability density functions to different atmospheric dynamics
- Implement and test the new model with toy problems
- Implement and test the new model with the WRF test cases
- Convert the Weather, Research, and Forecasting Gridpoint Statistical Interpolation (GSI) and the hybrid system to allow for a lognormal component (e.g., for the moisture variable) version with the logarithmic transform approach
- Test and compare the different versions of the WRF-GSI against different distributed error scenarios
- Conduct WRF-GSI experiments to assess the impacts on short and medium range forecasts from the different configurations of the hybrid WRF-GSI system
- Prepare manuscripts for submission to peer review journals and edit through the review process
Qualifications for data & applied scientist
- Ability to build production grade machine learning enabled solutions end to end
- Dimension Reduction
- Expert level programming skills in R
- Experience with a statistical package and various programming languages such as R, Python, Java, C++, SAS, Matlab
- Business Intelligence experience (Microsoft Power BI / Tableau)
- Experience writing SQL queries and linking to enable read/write to the database
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Data & Applied Scientist Job Description
Job Description Example
Our company is looking for a data & applied scientist. Thank you in advance for taking a look at the list of responsibilities and qualifications. We look forward to reviewing your resume.
Responsibilities for data & applied scientist
- Partner with internal teams to identify and explore opportunities for the application of machine learning and predictive analysis
- Deploy production grade machine learning models
- Prepare and present conference abstracts, posters, and/or presentations
- Travel to domestic and international conferences
- Design and implement changes in the forecasting systems and processes to incorporate rapidly-changing business strategies
- Create and maintain systems capable of extracting log-level detail from remote systems, transforming data to a common taxonomy, and autonomously feeding common insights
- Lead with data, informing executive-level decision-making with a minimum viable approach
- Work on training and refining various models to attain a high bar of required accuracy needed in healthcare
- Work with data engineers to architect and develop operational models that run at scale
- Design, prototype, implement and test descriptive and predictive analytics models
Qualifications for data & applied scientist
- Neural Networks (Feed-forward, CNN, RNN)
- Parallel Processing (CPU & GPU)
- Experimented - requires 7+ year’s experience in data analytics/data mining in a large enterprise
- Knowledgeable about data quality, data architecture, data management, data governance
- Bachelor’s degree in quantitative field (typically computer science, mathematics, engineering, physics, econometrics, political science, operations research, or applied statistics)
- Experience in major analytics/data mining software packages and programming languages/environments