Data Scientist, Senior

Company Federal Reserve Bank of Boston As an employee of the Boston Fed, you will work to promote sound growth and financial stability in New England and the nation. You will contribute to communities, the region, and the nation by conducting economic research, participating in monetary policy-making, supervising certain financial institutions, providing financial services and payments, playing a leadership role in the payments industry, and supporting economic well-being in communities through a variety of efforts. The Boston Fed is one of 12 Reserve Banks and we serve all or parts of Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont. Our mission is accomplished through our Bank's values: community, innovation, integrity, trust, leadership, and excellence. Job Summary 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 will inform economic policy. Working in close collaboration with IT Services leadership, this position will manage the full cycle of complex Research data and technology projects, working with junior staff to execute while utilizing a variety of data platform tools and methods. Principal Accountabilities 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. Supervision This position is not required to directly supervise others but may provide direction to junior team members or interns. Knowledge and Experience 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. Additional Knowledge and Experience -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 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 dat