Data Scientist, Senior

Federal Reserve Bank of Philadelphia • Boston, MA

4d

About The Position

As a Senior Data Scientist in the Research Data and Technology Solutions team at the Boston Fed, you will play a pivotal role in analyzing complex economic data to uncover trends, patterns, and insights that drive policy recommendations and business strategies. You will collaborate closely with cross-functional teams, including economists, engineers, analysts, and research stakeholders to develop and implement data-driven strategies and solutions. Your work will advance economic research, monetary policy, reports, publications, and presentations that have a direct impact on economic policy and market behavior. Working in close collaboration with IT Services leadership, this position will manage the full cycle of complex Research projects, working with junior staff to execute while utilizing a variety of data platform tools and methods.

Requirements

• Education: B. Sc. Computer Science or Statistics or Mathematics. Advanced degree or relevant experience preferred.
• Experience: Minimum of 5 years of experience in data science including machine learning, deep learning, and advanced analytics
• Technical Skills: Proficiency in modern statistical and general-purpose programming languages. Expertise in data analysis, machine learning, and statistical modeling. Experience with data visualization tools and big data technologies.
• Analytical Skills: Strong problem-solving abilities with a deep understanding of statistical methods and data analysis techniques. Ability to interpret complex data and communicate insights effectively.
• Communication: Strong verbal and written communication skills. Ability to present complex technical concepts to non-technical stakeholders.
• Collaboration: Proven experience working in a cross-functional team environment and building strong relationships with stakeholders.
• All candidates must be U.S. citizens or lawful permanent resident aliens with at least three or more years of U.S. residency from the date of legal entry to the U.S.
• For this job, any offer of employment is contingent upon successfully passing a two-phase security screening. The first phase consists of the satisfactory completion of a physical examination (including a drug screening), reference checks, and a security investigation consisting of credit and criminal history checks. The second phase, which might not be complete until after you begin working at the Reserve Bank, is an additional risk-based security screening determined by the risk rating of the position.
• All employees assigned to this position will be subject to FBI fingerprint/ criminal background and Patriot Act/ Office of Foreign Assets Control (OFAC) watch list checks at least once every five years.

Nice To Haves

• Tools and Technologies: Successful candidates will have expertise in the following.
• Programming languages: Python, R, Stata, SQL
• Frameworks: Apache Spark, Apache Airflow
• Cloud services: AWS (Lambda, EC2, ECS, IAM, Athena, S3)
• Deployment tools: Ansible, Terraform
• Operating systems: Linux (Alma, Red Hat)
• Statistical methods: Descriptive statistics, generalized linear models, basic econometrics
• Machine learning methods: Ability to translate a business or research problem into a model that can be trained or estimated. Common domains include clustering, regression, and neural networks. Familiarity with LLMs, parameter efficient fine-tuning, and RAG.
• Development tools: Git, GitLab

Responsibilities

• Project Management : Manage data science projects from inception to completion. Ensure timely delivery of high-quality results that meet business requirements.
• Data Analysis and Modeling: Maintain a thorough understanding of a variety of tools and methods to answer a broad range of research questions from complex datasets. Design and implement advanced statistical models, machine learning algorithms, and data processing techniques.
• Software Engineering: Design and develop software that enable research into modular, efficient, reusable, and maintainable scripts or packages.
• Collaboration: Work closely with economists and other stakeholders to understand their data needs and deliver solutions that drive business outcomes. Develop and promote best practices for reproducible research workflows. Communicate findings and recommendations effectively.
• Innovation: Stay current with industry trends and emerging technologies. Identify opportunities for incorporating new methods and technologies into our data science practices.
• Data Management: Implement data collection, storage, and processing pipelines to ensure data quality and integrity. Implement best practices for data governance and security.
• Reporting and Visualization: Develop and maintain dashboards, reports, and visualizations that provide clear and actionable insights to stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level