Data Scientist - DCCA

Minimum Education

Bachelor's degree or equivalent experience

Minimum Experience

5

Summary

Conducts statistical and mathematical initiatives to predict future outcomes through the application of machine learning, natural language processing, and conceptual modeling. Uses existing algorithms to test hypotheses through careful and deliberate model design. Conducts statistical analysis, modeling, and simulation that leads to actionable decisions. Applies statistical methods to characterize uncertainty using large, complex datasets. Utilizes data mining techniques to optimize decisions that support Division strategic objectives. Transforms data into actionable information.

Duties and Responsibilities

• Responsible for the collection and refinement of data from multiple high-volume data sources. Gathers and transforms large volumes of data from internal and external systems in a manner suitable for analysis.

• Works with large and complex data sets to solve difficult and non-routine problems. Performs data analysis in support of ad-hoc and standing requests.

• Participates on analytical research projects through all stages including concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.

• Leverages large datasets while thinking strategically about uses of data. Uses analytic models and works closely with cross-functional teams and people to integrate solutions.

• Conducts data studies and data discovery initiatives using existing and new data sources.

• Performs data quality tests and suggests new methods to improve statistical inferences of variables across models.

• Visualizes and reports data findings using a variety of formats to enhance insight into complex issues. Communicates findings through internal reports and executive summaries.

• Compiles, reviews, and assesses information from academic journals, market sources, and other reports to maintain state-of-the-art knowledge in data analysis techniques.

• Design, build, and deploy interactive data science applications, dashboards, and analytical tools.
• Develop, validate, and implement statistical and machine learning models to support analytical and policy-related work using quantitative and qualitative data.
• Apply AI and natural language processing methods, including large language model tools where appropriate, for tasks such as text analysis, classification, summarization, and information extraction.
• Support data ingestion, transformation, validation, and maintenance of structured and unstructured data pipelines and analytical datasets.
• Create clear visualizations, reports, and presentations to communicate findings to technical and non-technical audiences.
• Participate in analytical research projects and collaborate with staff across the division to identify, evaluate, and address complex business and policy questions.

• Proficiency in Python or R; experience with SQL and data extraction, transformation, and pipeline development.
• Knowledge of statistical methods, machine learning techniques, and model validation.
• Experience developing analytical applications, dashboards, or APIs and using software development best practices such as version control, testing, and documentation.
• Experience with data visualization tools and libraries such as Tableau, Power BI, Shiny, Plotly, ggplot2, or Matplotlib.
• Experience with GenAI coding assistants and experience integrating LLM APIs into applications.
• Knowledge of prompt engineering, RAG systems, or LLM fine-tuning.
• Familiarity with vector databases and semantic search.

• Strong problem-solving, critical thinking, and analytical abilities.
• Strong written and verbal communication skills for technical and non-technical audiences.
• Ability to work independently, manage multiple priorities, and contribute to collaborative projects.
• Dedication to continual learning and adapting to new tools and technologies.
• Desire to innovate and proactively finds way to deliver results on new and complex projects.

• Topical knowledge in consumer finance is preferred but not required. Relevant experience includes:

• Work with consumer financial data (credit reporting, mortgage, consumer loans)
• An understanding of financial services, banking regulations, or consumer protection
• Work in a regulatory or policy-oriented environment

• Must demonstrate knowledge and competence in the application of advanced theoretical and quantitative techniques in Data Science, Statistics, Mathematics, Computer Science, or other quantitative discipline typically achieved by completion of a bachelor’s degree plus five years of experience in applied statistical data analysis, survey management or equivalent combination of training and experience.
• Completes assignments from senior management and official staff with considerable independence. Reviews the work of others for technical soundness and accuracy.
• Work output contributes to the planning and organizing of the section’s work, independently anticipating issues requiring further analysis.
• Works with a high degree of independence in planning, organizing, and completion work products. Ability to perform under time pressure and meet strict deadlines. Excellent judgment and problem-solving skills. Ability to use known resources to seek answers and must be able to use initiative. Develops solutions for data system issues and problems that do not have clear precedent.

• Must demonstrate knowledge and competence in the application of advanced theoretical and quantitative techniques in Data Science, Statistics, Mathematics, Computer Science, or other quantitative discipline typically achieved by completion of a bachelor’s degree plus six years of experience in applied statistical data analysis, survey management or equivalent combination of training and experience.
• Completes assignments from senior management and official staff with considerable independence. Reviews the work of others for technical soundness and accuracy.
• Work output provides exceptional insight into large and sometimes messy datasets that determine the planning and organizing of the division’s work. Creates solutions to complex issues and translates technical analysis and policy implications to senior staff, Reserve Bank staff, and the Board.
• Requires strong problem-solving skills to identify and develop solutions to unique, unfamiliar issues. Works with a high degree of independence in planning, organizing, and completion work products. Performs under time pressure and meet strict deadlines. Excellent judgment, problem-solving skills, and uses initiative. Develops solutions for data system issues and problems that do not have clear precedent.
• Demonstrates organizational skills to identity priorities, drive performance-based outcomes, and execute projects on schedule.

• This position is located in Washington, DC, and requires in-office presence.

• The expected salary range for this role is $128,600 - $190,900, which spans all the posted grades. Final offers are based on the grade for which you minimally qualify and are determined by experience and education, as well as internal and external factors.



• Application deadline: Friday, May 22, 2026, 11:59 PM ET