Principal Data Scientist
About The Position
Citizens Financial Group, Inc. (CFG) seeks a Senior Data Scientist for its Boston, Massachusetts location. This role involves analyzing credit risk valuation models, correlations, concentrations, rating migrations, and risk contributions. The Senior Data Scientist will develop econometric models with a strong conceptual foundation to support business needs, and collaborate with business line partners to embed and socialize these models, while also supporting ongoing requests. The position requires analyzing commercial lending portfolios to review trends that support applications models, exploring large datasets using advanced statistical and modeling tools, and extracting data directly from source systems. A key responsibility includes working with appropriate parties to resolve or remediate data quality issues, maintaining, reviewing, and adhering to the organization’s credit policy, and conducting constant monitoring and validation of underlying credit theories and methodologies. The role also supports the implementation of developed models, including third-party vendor solution tools for credit risk and other applications. Participation in peer review sessions and maintaining awareness of new advances in credit risk modeling techniques are essential to ensure the application of best practices to CFG credit risk models. Additionally, the Senior Data Scientist will maintain technical documentation of developed models and model implementations, and troubleshoot implemented models in both internal and third-party vendor solutions.
Requirements
- Master’s degree in Physics, Data Analytics, or related quantitative field and two (2) years of experience in the role or in a related position.
- Utilizing relational databases, statistical analysis programming languages, and software, including SAS Enterprise Guide, SQL, R, Stata, AWS RedShift and Python, to extract high volume and complex data from external databases, including Oracle.
- Performing exploratory data analysis in Datalake using Python & R.
- Developing predictive models by implementing data analysis and research, including time series analysis, regression analysis, categorical analysis, machine learning methods, advanced econometric techniques related to panel data analysis, and data imputation.
- Utilizing the underlying mathematical principles behind statistical methods to evaluate and interpret the results of predictive models in a reasonable manner.
- Utilizing advanced statistical programming and visualization software, including SAS, Python, R and , to create complex reports and graphs.
- Building back testing and benchmarking tools to monitor model performance in accordance with established ALM policy.
- Implementing complex computational methods and models using R, SAS and Python.
- Standardizing, harmonizing, cleaning, preparing, and using data for developing datasets, reporting and analysis.
- Utilizing SQL Tools including Oracle and SQLite.
- Building pilot solutions and performing proof of concept for business problems using technologies including Graph Databases.
- Utilizing distributed computing and cloud software, including Amazon Web Services and Sage Maker.
- Utilizing version control tools, including Git, to develop reproducible code.
- Utilizing Command line interface and Shell Scripting languages to optimize workflows.
- Utilizing Package Version management software, including Anaconda.
- Utilizing IDEs, including VS Code, RStudio, Jupyter, and JupyterLab.
- Utilizing Documentation tools, including LATEX and RMarkdown.
Responsibilities
- Analyze credit risk valuation models, correlations, concentrations, rating migrations, and risk contributions.
- Develop econometric models built on solid conceptual foundation that supports business needs.
- Work with business line partners in embedding and socializing econometric models and support with on-going requests.
- Analyze commercial lending portfolios to review trends that support applications models.
- Explore large data sets using advanced statistical and modeling tools and pull datasets directly from source systems.
- Work with appropriate parties to resolve or remediate data quality issues.
- Maintain, review, and adhere to organization’s credit policy.
- Conduct constant monitoring and validation of underlying credit theories and methodologies.
- Support implementation of developed models, including third party vendor solution tools for credit risk and other applications.
- Participate in peer review sessions and maintain awareness of new advances in credit risk modeling techniques to ensure the application of best practices to CFG credit risk models.
- Maintain technical documentation of developed models and model implementations.
- Troubleshoot implemented models in both internal and third-party vendor solutions.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
