Lead Data Scientist

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 the Lead Data Scientist, you will be responsible for spearheading our data science projects and guiding a team of data scientists and engineers. You will collaborate closely with cross-functional teams, including engineering, IT, and research stakeholders, to develop and implement data-driven strategies and solutions. Your expertise will help shape our data science vision and drive impactful insights and innovations. This position will serve as a technical leader for a group of Data Scientists and will collaborate with Dev Ops Engineers to implement data platforms and analytics solutions.

Principal Accountabilities

Leadership and Strategy:
Lead and mentor a team of data scientists and engineers. Define and drive the data science strategy in alignment with department goals. Foster a culture of continuous learning and improvement within the team.

Project Management:
Oversee and manage multiple data science projects from inception to completion. Ensure timely delivery of high-quality results that meet business requirements.

Software Engineering:
Design and develop software that enable research into modular, efficient, reusable, and maintainable scripts or packages.

Data Analysis and Modeling:
Design and implement advanced statistical models, machine learning algorithms, and data processing techniques. Utilize a variety of tools and methods to answer research questions from complex datasets.

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:
Oversee data collection, storage, and processing 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:

Minimum

B. Sc. Computer Science with Statistics or Mathematics. Advanced degree preferred.

Experience:

Minimum of 7 years of experience in data science, including at least 3 years in a technical leadership role. Proven track record of successfully leading data science projects and teams.

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.

Additional Knowledge and Experience

Tools and Technologies:
Successful candidates will have familiarity with a number of tools listed below and ideally expertise in one or more.

* 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, Git Lab

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.

Leadership:
Demonstrated ability to lead, motivate, and mentor a team of data professionals. Excellent organizational and project management skills.

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…