Senior/Staff/Principal Data Scientist (HHS)

About Skylight

Skylight is a digital consultancy using design and technology to help government agencies deliver better public services. 

We’re at the forefront of a civic movement to reinvent how all levels of government serve families, patients, and many others in today’s digital world.

If you want to play a part in driving this critical movement forward, we’d love for you to join our growing team of public interest technologists. 

The work we do matters.

About the job

At Skylight, data scientists organize, synthesize, and analyze data to help government stakeholders and product teams make informed decisions. They apply a variety of analytical models to find meaningful insights in both structured and unstructured data, and they communicate these insights in an easily digestible format.

This project supports the HHS Office of the Chief Data Officer (OCDO) in modernizing enterprise data management, improving data accessibility, and strengthening coordination across HHS Divisions. The team provides end-to-end delivery—from discovery and roadmap development through engineering, implementation, and ongoing operations—across three core areas: the HHS Data Inventory, the AI Use-Case Inventory, and OCDO strategic and programmatic support.

Key activities include automating metadata collection and validation, expanding inventory coverage, supporting data catalog modernization and migration, coordinating Division data calls, and publishing public inventories. The team also supports data governance, statutory reporting, executive communications, and analytical needs. Together, these efforts help HHS reduce data silos, improve visibility into data and AI assets, meet federal reporting requirements, and establish sustainable infrastructure and processes for enterprise data sharing.

In this role, you’ll focus on the AI Use-Case Inventory and broader OCDO priorities, turning ambiguous policy and reporting requirements into practical, repeatable analytical workflows.

What to know going in

This is early-stage, high-visibility work with shifting priorities. Decisions often arrive unresolved, and you’ll help shape them rather than execute against a fixed spec. Client leadership believes moving too slowly is a bigger risk than being wrong, so you’ll do well here if you like prototyping quickly and sharing early, imperfect work.

You’ll work alongside a broader Skylight team. In your first 30 days, you’ll get access to existing systems, learn the current workstreams, and start contributing analysis to them.

What you’ll do

• Develop repeatable data quality checks, validate schemas, and standardize metadata across HHS’s data and AI inventories
• Evaluate, classify, and document risks for enterprise AI use cases in accordance with federal and agency governance standards
• Clean, integrate, and analyze complex data from multiple sources to surface trends, gaps, and patterns
• Apply machine learning and natural language processing to automate data tagging, classification, and metadata enrichment
• Prepare reporting datasets and turn findings into clear dashboards and recommendations for technical and executive audiences
• Choose the right tool for the job, whether that’s a straightforward analysis, a simple automation, or a model, with a preference for open-source solutions
• Collaborate with product managers, designers, engineers, and other specialists as part of a cross-functional team

What we’re looking for

Basic qualifications

• Experience working with AI systems, modern AI tooling, and enterprise AI model workflows
• Background in metadata standards, data profiling, and schema validation
• Can think about and use data strategically to identify the right questions to ask, communicate ideas, surface opportunities, and drive decisions
• Strong proficiency in Python and SQL, with hands-on experience  cleaning, validating, and preprocessing data from diverse sources
• Ability to analyze a data set using the appropriate analytical method, and to design, prototype, and build statistical models that are credible, effective, and accessible
• Ability to preserve privacy and security when performing data analysis
• Can articulately communicate your data, models, and findings to technical, non-technical, and executive audiences
• Ability to use the appropriate visualization tools to highlight actionable insights, trends, and recommendations from data
• Champion leading practices within data science to your team and others
• Experience working on cross-functional teams (product, design, engineering, ops) in iterative delivery
• A mindset and work approach that aligns with our core values

Nice-to-haves

• Experience conducting risk assessments, evaluations, and compliance classifications for AI use cases against federal or industry frameworks
• Strong data engineering skills, including working directly in backend pipeline code, ETL workflows, and metadata processing
• Practical experience applying AI, machine learning, and natural language processing to automate data tagging, classification, and metadata enrichment
• Familiarity with federal data governance, AI governance, enterprise AI model inventories, or open data reporting
• Proficiency with Power BI
• Experience delivering technology in government, regulated industries, or other public-benefit settings
• A track record of staying aligned and accountable on remote teams