Quantitative Analytics Senior Resume Samples

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A Huel
Anibal
Huel
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+1 (555) 255 7366
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NY
Phone
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Experience Experience
Phoenix, AZ
Quantitative Analytics Senior
Phoenix, AZ
Jaskolski LLC
Phoenix, AZ
Quantitative Analytics Senior
  • Generate complex statistical analyses using large data sets
  • Write and update model documentation by working with model users and other stakeholders
  • Coordinate the testing through the model implementation, conducting back tests to monitor the model performance, performing sensitivity tests to validate the model results
  • Develop models on PD and LGD for use in DFAST and risk management processes
  • Manage model applications, create analysis and interpret model output and conduct research related to the credit loss forecast methodology
  • Execute models and develop credit loss forecast, under various economic scenarios and including those under Dodd-Frank Act Stress Test (DFAST)
  • Quickly frame analytic problems/issues, solve them by modeling risk simulation scenarios using statistical analysis, and package results, often under tight deadlines
Boston, MA
Quantitative Analytics Senior
Boston, MA
Abernathy LLC
Boston, MA
Quantitative Analytics Senior
  • Developing analytical methods and quantitative models for market and credit risks of new and existing financial and mortgage products/portfolio
  • Implementing strategic policies when selecting methods, techniques, and evaluation criteria for obtaining results
  • Reviewing and updating model documentation (model performance, user guide, policy documents, etc.); developing validation reports based on rigorous theoretical and analytical reviews of models
  • Familiar with regression models, stochastic process modeling, and Monte-Carlo simulation
  • Develop analytical models and methods used to value and hedge mortgage securities and loans
  • Provide modeling, analytical, and data support to trading desks
  • Work under limited direction, independently determining and developing approach to solutions
present
Houston, TX
Quantitative Analytics Senior A
Houston, TX
Towne, Schaden and McGlynn
present
Houston, TX
Quantitative Analytics Senior A
present
  • Create and implement algorithms in graph and network analysis
  • Providing modeling and analytical support to a line of business or product area
  • Writing and updating model documentation by working with models’ users and other stakeholders
  • Working with Model Validation and Audit during periodic evaluations of model design, use and implementation
  • Apply Data Mining/Machine Learning algorithms to solve business problems
  • Expert of Data Mining, Machine Learning and related algorithms
  • Conducting complex data and statistical analysis on both model inputs & model outputs
Education Education
Master’s Degree in Economics
Master’s Degree in Economics
Carnegie Mellon University
Master’s Degree in Economics
Skills Skills
  • Detail oriented. Excellent communication skills (verbal and written)
  • Strong knowledge of econometric models, tools and techniques
  • Strong analytical skills with orientation to detail
  • Good writing skills and strong interpersonal and communication skills
  • May perform detailed model validation reviews, establishing performance thresholds, researching model approaches, creating alternative models and other means
  • Substantial knowledge and experience with forecasting economic or financial markets
  • Substantial knowledge of financial instruments, market structure, macroeconomic theory, and monetary policy
  • Working knowledge of Excel, PowerPoint, Visio
  • Comfortable working with large data sets
  • Demonstrated knowledge of stochastic calculus and one or more of valuation models, term structure models, and economic capital models
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4 Quantitative Analytics Senior resume templates

1

Quantitative Analytics Senior Resume Examples & Samples

  • Master’s degree in Economics, Finance, Statistics or related field or Bachelor’s degree plus 5 years relevant work experience (in economics, finance, or the mortgage industry)
  • Strong written and oral communication skills and experience with quantitative analysis (e.g. statistics/econometrics)
  • Excellent written and verbal communication skills; ability to extract larger themes while providing concise, articulate, and insightful analysis in both written and verbal form
  • Ability to succinctly communicate industry and company performance, key implications and trends
  • Strong interpersonal skills and ability to interact and collaborate effectively with team members, peers, senior management, and external parties
  • Ability to analyze complex market issues, make decisions quickly, and respond under pressure
  • Strong attention to detail and ability to anticipate and resolve issues as they arise
  • PhD in Economics, Finance, Statistics, or related field
  • Experience in mortgage finance or real estate
  • Proven ability in working with and understanding economic and financial data
  • Substantial knowledge of financial instruments, market structure, macroeconomic theory, and monetary policy
  • Familiarity with mortgage-related markets and/or financial market transactions
  • Substantial knowledge and experience with forecasting economic or financial markets
  • Familiarity with time series econometrics and macroeconomic forecasting models
2

Quantitative Analytics Senior Resume Examples & Samples

  • PhD in Economics, Statistics, or a directly related quantitative field or MS with at least three years of related post-graduate work experience
  • Strong programming skills in statistical programming languages such SAS, R, and Matlab
  • Experience in using complex statistical models such as Generalized Additive Models, transition models, and logistic regression
  • Programming experience with SAS, R and Matlab
  • Experience with competing-risk hazard models and transition-based models
  • Experience working with large data sets
3

Quantitative Analytics Senior Resume Examples & Samples

  • Advanced degree (PhD, Masters) in a quantitative discipline (data science, statistics, computer science, economics/econometrics, applied mathematics, operational research, physics, bioinformatics, engineering, etc.) or a Bachelors degree with equivalent experience
  • Experience using Hadoop and related technologies (Spark, Hive, etc.)
  • Experience querying relational databases via SQL Experience querying relational databases via SQL
4

Quantitative Analytics Senior Resume Examples & Samples

  • Developing analytical methods and quantitative models for market and credit risks of new and existing financial and mortgage products/portfolio
  • Implementing strategic policies when selecting methods, techniques, and evaluation criteria for obtaining results
  • Reviewing and updating model documentation (model performance, user guide, policy documents, etc.); developing validation reports based on rigorous theoretical and analytical reviews of models
  • At least 3 years of financial modeling related work experience and an advanced degree (PhD preferred) in Economics, Finance, Statistics, Engineering, or a directly related quantitative field
  • Programming experience with C++ or Matlab
  • Familiar with regression models, stochastic process modeling, and Monte-Carlo simulation
  • Asset-liability management (ALM) experience
  • Experience with valuation and risk analytics of fixed-income products, e.g., mortgage backed securities
  • Experience related to accounting practice
5

Quantitative Analytics Senior Resume Examples & Samples

  • Develop analytical models and methods used to value and hedge mortgage securities and loans
  • Provide modeling, analytical, and data support to trading desks
  • Work under limited direction, independently determining and developing approach to solutions
  • Generate complex statistical analyses using large data sets
  • Write and update model documentation by working with model users and other stakeholders
  • Coordinate the testing through the model implementation, conducting back tests to monitor the model performance, performing sensitivity tests to validate the model results
6

Quantitative Analytics Senior Resume Examples & Samples

  • Develop models on PD and LGD for use in DFAST and risk management processes
  • Manage model applications, create analysis and interpret model output and conduct research related to the credit loss forecast methodology
  • Execute models and develop credit loss forecast, under various economic scenarios and including those under Dodd-Frank Act Stress Test (DFAST)
  • Research and analyze key drivers related to loss reserves and credit loss forecast. Manage and execute existing data preparation processes
  • Perform ad hoc analysis to identify risk and work on issues of diverse scope where analysis of situation or data requires evaluation of a variety of factors, including an understanding of current business trends
  • Bachelors degree or equivalent experience; advanced studies/degree preferred with a least 5 years related experience
  • OR MS in Economics, Statistics, or a directly related quantitative field with at least 3 years of related post-graduate work experience in quantitative finance
  • PhD in economics or statistics
  • Knowledge of Single Family mortgage business and/or servicing
7

Quantitative Analytics Senior Resume Examples & Samples

  • Report findings to model owners and management, and ensure those findings are addressed appropriately
  • Working with model developers and users to manage model risks
  • PhD in Finance, Computational Finance, Economics, Mathematics, Physics, Statistics or a directly related quantitative field
  • OR MS in Financial Engineering, Economics, Statistics, Quantitative Finance, or a directly related quantitative field with at least 3 years of related post-graduate work experience in quantitative finance or risk management
  • Demonstrated knowledge of stochastic calculus and one or more of valuation models, term structure models, and economic capital models
  • Programming skills in one or more of SAS, MATLAB, C++, or related languages
8

Quantitative Analytics Senior Resume Examples & Samples

  • Developing analytical methods and models that assess the credit risk of new and existing financial and mortgage products
  • Providing innovative, thorough and practical solutions to an extensive range of demanding and complicated problems
  • Working under limited direction, independently determining and developing approach to solutions
  • At least one year of experience in model development including logistic regression
  • Strong programming skills in SAS
  • Strong knowledge of econometric models, tools and techniques
  • Experience with competing-risk hazard models, transition models, loss forecasting and stress testing
  • Experience working with consumer credit risk models, i.e. mortgage, credit card, or automotive
9

Quantitative Analytics Senior Resume Examples & Samples

  • Detailed review of models related to residential mortgage loans, securities and structured products
  • PhD in Economics (preferably Micro or Econometrics), Statistics, Computational Finance or a related quantitative field such as physics or engineering
  • OR MS in Economics, Statistics, Quantitative Finance, or a directly related quantitative field with at least 3 years of related post-graduate work experience in quantitative finance or risk management
  • Experience with parameter estimation methods
  • Excellent econometric modeling and SAS programming skills
  • Demonstrated knowledge of development and/or validation statistical or econometric models
  • Experience with one or more of multinomial logistic regression techniques, hazard models, stochastic calculus, or knowledge of mortgage analytics
  • Previous modeling related research or internships, in addition to significant coursework and post-doctoral research in quantitative fields
10

Quantitative Analytics Senior Resume Examples & Samples

  • Support the group’s mortgage quantitative research initiatives and utilize economic capital models to assess asset-specific and portfolio risk
  • Use existing corporate models and quantitative approaches to assess risk of portfolio holdings
  • Support development of capital allocation for new products and initiatives, by utilizing various approaches including sensitivity analyses, stress testing, value-at-risk, scenario testing, and Monte Carlo simulations
  • Support maintenance of group’s models per established corporate and department model governance policies and procedures
  • Develop documentation of department’s models and procedures
  • Strong background in developing computing models that apply sophisticated analytical techniques . Ability to extract and analyzing raw data and statistical model output draw conclusions and make actionable recommendation
  • At least 7 years of functional and industry experience in quantitative risk modeling
  • Technically and quantitatively oriented with proven ability to thoroughly understand external technical research
  • Solid understanding of the fixed income market and securities
  • Advanced statistical programming skills (Matlab, Mathematica, SAS or similar) plus advanced knowledge of Microsoft Excel
  • Understanding of mortgage credit default and prepayment models and loss mitigation activities
  • Working knowledge on mortgage and insurance industry
  • Exposure to Basel or Solvency II regulatory capital requirements
  • Good presentation skills
11

Quantitative Analytics Senior Resume Examples & Samples

  • Developing analytical approaches that measure credit risk and economic capital in multifamily debt investments and commercial mortgage products
  • Leveraging quantitative abilities – both data management and statistical analytic s – to provide analytical support to the multifamily mortgage business
  • PhD in Economics, Statistics, or a directly related quantitative field and at least one year of previous data analysis related work or internships, in addition to significant coursework and research in quantitative fields
  • Good communication, interpersonal, and teamwork skills
  • Experience working with consumer credit risk models, i.e. mortgage, credit card, automotive, or other consumer lending models
  • Strong preference for applicant with a sound real estate finance and economics experience / background
12

Quantitative Analytics Senior A Resume Examples & Samples

  • Implement the applicable Machine Learning or statistics based algorithm for prediction and optimization and deliver the trained model to production
  • Create and implement algorithms in graph and network analysis
  • Ph.D. in Computer Science or equivalent field
  • At least 2 years of experience in machine learning
  • Experience with Graph/Network analysis
  • Experience with Hadoop stack (HIVE, Pig, Hadoop streaming) and MapReduce
  • Expert of Data Mining, Machine Learning and related algorithms
  • Proficient in two of the languages: Java, Python, Scala, C++, C#
  • Independent/innovative thinking
  • Industrial experience in quantitative finance
13

Quantitative Analytics Senior Resume Examples & Samples

  • Bachelor’s degree or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, computer science or related quantitative discipline followed by five (5) years of experience with economic and/or financial modeling, which includes experience with: modern econometric/statistics estimation techniques; programming in SAS,R ,Matlab and/or C++; and, working with large data sets OR
  • Master’s degree or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, or computer science or related quantitative discipline and three (3) years of experience with economic and/or financial modeling, which includes experience with: modern econometric/statistics estimation techniques; programming in SAS, R, Matlab and/or C++; and, working with large data sets OR
  • Ph.D. or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, or computer science or related quantitative discipline and demonstrated knowledge of economic and/or financial modeling, including: modern econometric/statistics estimation techniques; programming in SAS, R, Matlab and/or C++; and, working with large data sets. Knowledge may be demonstrated through education, training and/or hands-on experience
  • Experience building and/or validating econometric models
  • Knowledge of or experience in capital markets, asset and liability management, general understanding of primary and secondary mortgage market, or counterparty risk
  • Big 4 consulting or auditing experience
  • Familiarity with the role of Internal Audit and SOX controls
14

Quantitative Analytics Senior Resume Examples & Samples

  • Develop, use and/or analyze quantitative models that assess the market, credit and/or operational risks of new and existing financial and mortgage products or portfolios to support business and risk decisions
  • Develop, validate or evaluate model input, methodology, implementation and output of models or analytic applications
  • May plan, execute, and document complex financial models
  • May provide model use risk assessments based on findings
  • Evaluate and manage risks associated with the company's models and/or model applications
  • May perform detailed model validation reviews, establishing performance thresholds, researching model approaches, creating alternative models and other means
  • May explain to stakeholders how a model and model process operates, what risks are inherent in the model or model process, and what controls exist to mitigate those risks
  • May interact with senior customer personnel on significant technical matters frequently requiring coordination across organizational lines
  • Bachelor’s degree or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, computer science or related quantitative discipline followed by five (5) years of experience with economic and/or financial modeling, which includes experience with: modern econometric/statistics estimation techniques; programming in SAS,R ,Matlab and/or C++; and, working with large data sets
  • Experience with programming language such as Python, R, Matlab, VBA, Java and C++ or related languages
  • Good communication, interpersonal skills
15

Quantitative Analytics Senior Resume Examples & Samples

  • Master’s degree in Economics, Finance, Statistics or related field plus 5 years of relevant work experience (in economics, finance, or the mortgage industry)
  • Experience with data analysis, statistical modeling, and/or financial valuation
  • Familiarity with cross-sectional and panel econometrics
  • Experience with specific programming languages, such as SAS and R, is highly desirable, but not required. Experience in UNIX and the ability to use software to create, modify, and access databases is also desirable
16

Quantitative Analytics Senior Resume Examples & Samples

  • Evaluates the design and operating effectiveness of model policies, standards, and model development procedures
  • Evaluates how effectively model controls are designed and operating and use this information to test the process, document work papers, make recommendations for improvements, and draft reports detailing the team’s conclusions
  • Operates independently and is the primary person responsible for immersing themselves in a process or group of processes
  • Must be able to explain, after a relatively short time, how a model process operates, what risks are inherent in the model process, what controls exist to mitigate those risks
  • Assists in preparing project planning and closure documents
  • Supervises the day to day operations for a single project, including an audit, follow up, or pre-implementation review
  • Supports a team of PhD economists or mathematicians in evaluating model risk
  • Working knowledge of Excel, PowerPoint, Visio
  • Good writing skills and strong interpersonal and communication skills
  • Interest in developing quantitative, empirical analysis, research and computer programming skills
  • Interest in or completing an economics or quantitative graduate degree
  • CIA certification
  • Modeling technical skills at the Master’s level
  • Willingness to learn basic modeling concepts
17

Quantitative Analytics Senior Resume Examples & Samples

  • Ongoing monitoring of model performance including back-testing, benchmarking, stress-testing and the assessment of model assumptions, limitations and input data quality
  • Independent validation of model and model-related code, data and process
  • Ad-hoc analysis involving new models, model changes, model performance, the Retained portfolio and data sources used for model estimation and testing
  • Assist, when necessary, in the drafting of model documentation including developer and user guides, change management memos and data dictionaries
  • Impact analysis (to the Retained portfolio) of model changes, on-top adjustments, forecast updates and methodological changes
  • Testing of new databases, connectivity protocols and analytical tools in the Enclave (big data) environment, including validation of new table schemas and data loads
  • Present ongoing monitoring and analysis at meetings of model community
  • Master’s/Bachelor’s degree in applied mathematics, economics, statistics, computer science, finance or related quantitative discipline and three/at least five (3, 5+) years of experience with economic modeling which includes experience with logistic regressions, hazard models and modern econometric/statistics estimation techniques
  • Experience programming in SAS and SQL
  • Experience programming in R, Python or Matlab
  • Experience with scripting in Linux and Windows
  • Experience with reporting and data visualization tools such as Tableau
  • Experience working with prepayment, default, interest rate and HPA models
  • Experience using the Workbench tool specifically the Mortgage Pricer application
  • Experience with the Green Package management information system including Anser
  • Experience using the eMBS, Core Logic and Atlas databases
18

Quantitative Analytics Senior A Resume Examples & Samples

  • Creating counterparty credit risk models related to estimation of probability of default (PD), Exposure at Default and Loss given default (LGD) to generate Ratings of financial institutions in normal and stress conditions (DFAST)
  • Updating/calibrating existing models
  • Writing and updating model documentation by working with models’ users and other stakeholders
  • Providing modeling and analytical support to a line of business or product area
  • Working with Model Validation and Audit during periodic evaluations of model design, use and implementation
  • Conducting complex data and statistical analysis on both model inputs & model outputs
  • Implementing enhancements or changes to models, working with IT, as appropriate
  • Understanding Freddie Mac’s internal Counterparty rating philosophy and methodological choices
  • Understanding the logic and math of the rating and exposure models, as well as the data that goes into them
  • Ph.D. or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, or computer science or related quantitative discipline and demonstrated knowledge of economic and/or financial modeling, including: modern econometric/statistics estimation techniques; programming in SAS, SQL, R, Matlab and/or C++; and, working with large data sets. Knowledge may be demonstrated through education, training and/or hands-on experience
  • Master’s degree or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, or computer science or related quantitative discipline and three (3) years of experience with economic and/or financial modeling, which includes experience with: modern econometric/statistics estimation techniques; programming in SAS, SQL, R, Matlab and/or C++; and, working with large data sets; OR
  • Solid quantitative, empirical analysis, and research skills
  • Strong economic/business intuition
  • Strong programming skills in statistical programming languages such as SAS, SQL, VBA. Knowledge of other languages such as R, Python and/or Matlab is a plus
  • At least two years of previous commercial credit risk modeling developing Commercial probability of default (PD), Loss Given Default (LGD), and Exposure at default (EAD) models, building counterparty Scorecards or DFAST/CCAR commercial risk models
  • Strong understanding of commercial finance products and risk management practices
  • Experience in using complex statistical models
  • Knowledge of Freddie Mac data and business is preferred but is not required
  • Ability to conduct independent research and work with limited supervision
19

Quantitative Analytics Senior Resume Examples & Samples

  • Data Engineering
  • Bachelor’s or Master’s degree in Statistics, Economics, Business, Mathematics, Computer Science or related field
  • 5+ years of experience in processing large volumes and variety of data (Structured and unstructured data, writing code for parallel processing, XMLS, JSONs, PDFs)
  • 3+ years of programming experience in at least 2 - R, Python, Spark, Java for data processing and analysis
  • 2+ years of experience – using Hadoop platform and performing analysis. Familiarity with Hadoop cluster environment and configurations for resource management for analysis work
  • Use of analytical and statistical functions (Standard deviation, decision trees) is preferred
  • Strong quantitative, analytical, and problem-solving skills
  • Detail oriented. Excellent communication skills (verbal and written)
  • Must be able to manage multiple priorities and meet deadlines
20

Quantitative Analytics Senior Resume Examples & Samples

  • PhD or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, or computer science or related quantitative discipline and demonstrated knowledge of economic and/or financial modeling, OR
  • Master’s degree or foreign equivalent in data science, applied mathematics, economics, physics, econometrics, finance, engineering, statistics, or computer science or related quantitative discipline and three (3) years of experience with economic and/or financial modeling
  • 3+ years of training in and/or experience with data science, statistics, and/or machine learning
  • 1+ years of training in and/or experience programming in either R or Python
  • 1+ years of training in and/or experience using Hadoop and related technologies (Spark, Hive, etc.)
  • Experience with and/or training in text mining for predictive analytics
21

Quantitative Analytics Senior Resume Examples & Samples

  • Use techniques from statistics, machine learning, and other data sciences to review predictive models with a growing variety of features (numeric, categorical, geographic, textual, or images)
  • Visualize data to communicate complex patterns to executives and business users
  • Develop In-depth knowledge of mortgage analytics
  • Responsible for evaluating risk associated with the company's models including models of default, prepayment, loan scoring, valuation, derivatives, interest rates, stress testing and counterparties
  • Conduct a detailed risk assessment, design and execute operational and technical audit procedures to provide assurance on controlled model development, on-going monitoring and business use
  • Provide thought leadership on key initiatives including execution of model risk management framework and quality improvement program
  • Provide instruction in data science concepts to other members of the MDA team
  • Develop strong working relationships with Data Science personnel in other areas of the business
  • PhD or foreign equivalent in statistics, data science, economics, finance, computer science or related quantitative disciplines with 2-3 years of experience
  • Master’s degree or foreign equivalent in statistics, data science, economics, finance, computer science or related quantitative disciplines with 4-6 years of experience
  • Possess expert knowledge of applied computer programming, preferably R, Python, SAS, MATLAB, and SQL
  • Working knowledge of Java and C++ preferred
  • Familiarity with outlier detection, cluster analysis, and global sensitivity analysis
  • Eagerness to adapt new data science techniques to improve data efficiency and effectiveness
  • Possession or willingness to pursue certifications in Internal Audit (CIA, CPA, CISA)