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.
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.

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.
In your first 30 days, you’ll get access to existing systems, learn the current workstreams, and start contributing analysis to them.
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
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
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 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
A track record of staying aligned and accountable on remote teams
Logistics
This is a full-time, exempt position.
This is a fully remote position.
Travel
This role may require occasional or regular travel based on company, client, or contract needs.
For a Data Scientist at Skylight, the current salary ranges are as follows:

Associate Data Scientist: $90,000–$125,000
Data Scientist I: $120,000–$140,000
Data Scientist II: $135,000–$160,000
Senior Data Scientist: $150,000–$185,000
Staff Data Scientist: $170,000–$203,000
Principal Data Scientist: $180,000–$230,000
Medical insurance, dental insurance, vision insurance
Short-term and long-term disability insurance
Life and AD&D insurance
Dependent care FSA, healthcare FSA, health savings account
Flexible paid-time-off policy (generally around 25 days per year), plus 11 paid federal holidays
Performance rewards, including annual salary increase, annual performance bonus, spot bonuses, and stock options
Business development / sales bonuses
Referral bonuses
Flexible, remote-friendly work environment
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All qualified applicants will receive consideration for employment without regard to race, color, national origin, sex, religion, age, disability, veteran status, or any other category protected by applicable law.