Line of Business Specific Job Description:
Data scientist and business architect responsible for independently conducting quantitative analytics, building process methodologies, and implementing output. Responsible for developing/implementing new models, analytic processes or systems approaches. Proactively documents measures of success and works across Operations and Technology teams to execute on data-driven recommendations. Functionally integrates advanced statistical theory with machine learning techniques to transform traditionally manual operations.
Packaging and communicating conceptual foundations of new and existing: models, model specifications, underlying assumptions, limitations, variable selection, underlying data, developmental evidence, and documentation.
Assessing quality of model outputs through back testing against realized outcomes, benchmarking against alternative models and other relevant tests.
Aligning the mechanics of implementation with LOB tactical execution timelines and strategic development.
Translating theory to practice and operationalizing sound methodologies in imperfect environments.
Enterprise Specific Job Description:
Responsible for developing quantitative/analytic models and applications in support of the firm's risk management effort. This role focuses on the development of operations/data management policies, strategies and operational guidelines for the organization's various financial products as they relate to the analysis, tracking, and reporting of various risk metrics. This role often possesses an advanced degree in physics, applied mathematics, statistics/probability or another heavy quantitative discipline. Quantitative analytic staff is focused on and responsible for the development of the theory and mathematics behind various models. Individual Contributor and reports to Quant Operations Manager
Master's degree in Statistics, Mathematics, Finance, Engineering, Physics, Economics or related field or equivalent experience.
Minimum 3 years of experience in computational, engineering or scientific research or development roles.
Minimum 3 years of programming experience using SAS.
Functional experience with relevant statistical methods, hypothesis testing, and advanced machine learning (specifically artificial neural networks).
Data development experience with: Oracle, Hadoop, Teradata, and SQL Server.
Strong knowledge of risk management principles.
Deep understanding and knowledge of model performance measures.
Experience in forecasting or quant group in a bank, financial institution or vendor.
Ability to communicate clearly and effectively.
Ability to produce high quality technical documentation.
Shift:1st shift (United States of America)
Hours Per Week:40
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