Principal Data Scientist (HHS)

Skylight

7d•$90,000 - $230,000•Remote

About The Position

Skylight is hiring a Data Scientist to support 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 delivers work from discovery and roadmap development through engineering, implementation, and ongoing operations across the HHS Data Inventory, AI Use-Case Inventory, and OCDO strategic and programmatic support. The role focuses on the AI Use-Case Inventory and broader OCDO priorities, translating ambiguous policy and reporting requirements into practical, repeatable analytical workflows. Work includes automating metadata collection and validation, expanding inventory coverage, supporting data catalog modernization and migration, coordinating Division data calls, publishing public inventories, and contributing to data governance, statutory reporting, executive communications, and analytical needs. The work aims to reduce data silos, improve visibility into data and AI assets, meet federal reporting requirements, and build sustainable enterprise data-sharing infrastructure and processes. This is early-stage, high-visibility work with shifting priorities. Decisions may be unresolved, and the successful candidate will help shape them by prototyping quickly and sharing early work. The employee will join a broader Skylight team, gain access to existing systems and learn current workstreams during the first 30 days, and begin contributing analysis. The role is fully remote, must be performed within the U.S. excluding territories, may require occasional or regular travel, and requires obtaining and maintaining a Public Trust clearance and successfully completing a company background check. Candidates must be legally authorized to work in the U.S. now and in the future without sponsorship. This is a full-time, exempt position.

Requirements

Experience working with AI systems, modern AI tooling, and enterprise AI model workflows.
Background in metadata standards, data profiling, and schema validation.
Ability to use data strategically to identify questions, communicate ideas, surface opportunities, and drive decisions.
Strong proficiency in Python and SQL, including hands-on experience cleaning, validating, and preprocessing data from diverse sources.
Ability to select appropriate analytical methods and design, prototype, and build credible, effective, and accessible statistical models.
Ability to preserve privacy and security when performing data analysis.
Ability to clearly communicate data, models, and findings to technical, non-technical, and executive audiences.
Ability to use appropriate visualization tools to highlight actionable insights, trends, and recommendations.
Ability to champion leading practices in data science.
Experience working on cross-functional teams involving product, design, engineering, and operations in iterative delivery.
A mindset and work approach aligned with Skylight’s core values.
Must be legally authorized to work in the U.S. now and in the future without sponsorship.
Must obtain and maintain a Public Trust clearance and successfully complete a company background check.
All work must be conducted within the U.S., excluding U.S. territories.

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 direct work 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.
A degree or additional years of experience may be required as a substitute for some federal-contract roles.

Responsibilities

Develop repeatable data quality checks, validate schemas, and standardize metadata across HHS 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 communicate findings through clear dashboards and recommendations for technical and executive audiences.
Select appropriate tools for analyses, automations, or models, with a preference for open-source solutions.
Collaborate with product managers, designers, engineers, and other specialists on a cross-functional team.
Support automation of metadata collection and validation, expansion of inventory coverage, data catalog modernization and migration, Division data calls, and publication of public inventories.
Contribute to data governance, statutory reporting, executive communications, and analytical needs.
Prototype quickly and share early work while helping shape decisions and workflows amid changing priorities.

Benefits

Medical insurance
Dental insurance
Vision insurance
Short-term and long-term disability insurance
Life and AD&D insurance
Dependent care FSA, healthcare FSA, and health savings account
Dollar-for-dollar 401(k) match up to 10% of salary, with no vesting period
Flexible paid-time-off policy, generally around 25 days per year
11 paid federal holidays
Up to 12 weeks of paid time off for eligible new birth, adoption, or foster parents
Annual salary increases
Annual performance bonus
Spot bonuses
Stock options
Business development and sales bonuses
Referral bonuses
Annual $2,000 professional development allowance
Annual $750 allowance for tech-related purchases
Annual $100 swag budget
Flexible, remote-friendly work environment