Senior/Staff/Principal Data Scientist (HHS)

Description

The company is a digital consultancy that uses design and technology to help government agencies deliver better public services.

It is a growing team of public interest technologists working on modernizing how all levels of government serve people.

Data scientists here organize, synthesize and analyze data so government stakeholders and product teams can make sound decisions. You will apply a range of analytical models to structured and unstructured data and present findings in a form people can quickly grasp.

The project supports the Office of the Chief Data Officer at HHS in modernizing enterprise data management, improving access to data and coordinating across HHS divisions. The team handles the full cycle, from discovery and roadmap through engineering, rollout and ongoing operations. Its three areas are the HHS Data Inventory, the AI Use-Case Inventory, and strategic and programmatic support for the OCDO.

Current work includes automating metadata collection and validation, widening inventory coverage, modernizing and migrating the data catalog, gathering data from divisions, publishing public inventories, and supporting governance, statutory reporting, executive communications and analysis. The aim is fewer data silos, better visibility into data and AI assets, compliance with federal reporting rules, and lasting processes for sharing data across the enterprise.

Your focus will be the AI Use-Case Inventory and wider OCDO priorities, turning vague policy and reporting requirements into practical, repeatable analysis workflows.

Expect early-stage work with shifting priorities. Decisions often stay open, and you will help shape them rather than follow a fixed spec. Client leadership sees moving too slowly as a bigger risk than being wrong, so the role suits people who like prototyping quickly and sharing rough early work. In your first 30 days you will get system access, learn the current workstreams and start contributing analysis alongside the wider team.

The hiring process runs about four conversations over two to three weeks: a preliminary screen, a skills interview, a behavioral interview, and a reverse interview where you meet your potential team.

Candidates who do not meet every qualification are still encouraged to apply.

To request reasonable accommodations during the application or interview process, contact the recruiting team.

Responsibilities

• Build repeatable data quality checks, validate schemas and standardize metadata across HHS data and AI inventories.
• Assess, classify and document risks for enterprise AI use cases under federal and agency governance standards.
• Work through messy data pulled from several sources, merging and analyzing it to find trends, gaps and patterns.
• Use machine learning and natural language processing to automate tagging, classification and metadata enrichment.
• Prepare datasets for reporting and present results as dashboards and advice that engineers and executives can act on.
• Pick the right approach for each problem, from a simple analysis or small automation to a model, favoring open-source tools.
• Work with product managers, designers, engineers and other specialists on a cross-functional team.

Requirements

• Basic qualification: hands-on work with AI systems, current AI tooling and enterprise AI model workflows.
• Basic qualification: knowledge of metadata standards, data profiling and schema validation.
• Basic qualification: you think strategically about data, asking the right questions, sharing ideas, spotting opportunities and supporting decisions.
• Basic qualification: strong Python and SQL, with practical experience cleaning, validating and preprocessing data from varied sources.
• Basic qualification: you can choose a suitable analytical method and design, prototype and build statistical models that are sound, effective and easy to understand.
• Basic qualification: you protect privacy and security during analysis.
• Basic qualification: you explain your data, models and findings clearly to technical, non-technical and executive audiences.
• Basic qualification: you can use visualization tools to show actionable insights, trends and recommendations.
• Basic qualification: you promote good data science practice within your team and beyond.
• Basic qualification: experience on cross-functional product, design, engineering and operations teams using iterative delivery.
• Basic qualification: a mindset and way of working that fit the company's core values.
• Nice-to-have: experience doing risk assessments, evaluations and compliance classifications of AI use cases against federal or industry frameworks.
• Nice-to-have: strong data engineering, including backend pipeline code, ETL workflows and metadata processing.
• Nice-to-have: practical experience applying AI, machine learning and NLP to automate tagging, classification and metadata enrichment.
• Nice-to-have: familiarity with federal data governance, AI governance, enterprise AI model inventories or open data reporting.
• Nice-to-have: proficiency with Power BI.
• Nice-to-have: experience delivering technology in government, regulated industries or other public-benefit settings.
• Nice-to-have: a track record of staying aligned and accountable on remote teams.

Conditions

This is a fully remote position.

This role may require occasional or regular travel, depending on company, client or contract needs.

This is a full-time, exempt position.

On some roles tied to federal contracts, a degree or additional years of experience can be used as a substitute.

All work must be performed within the U.S., excluding U.S. territories.

You must be legally authorized to work in the U.S. now and in the future, without sponsorship.

This role requires you to obtain and maintain a Public Trust clearance.

Pay is set from your interview results and your seniority level. Current salary ranges for Data Scientist roles are: Associate Data Scientist $90,000 to $125,000; Data Scientist I $120,000 to $140,000; Data Scientist II $135,000 to $160,000; Senior Data Scientist $150,000 to $185,000; Staff Data Scientist $170,000 to $203,000; Principal Data Scientist $180,000 to $230,000.

Benefits

• Medical, dental and vision insurance.
• Short-term and long-term disability insurance.
• Life and AD&D insurance.
• Dependent care FSA, healthcare FSA and a health savings account.
• 401(k) with a dollar-for-dollar match up to 10% of salary, and the match vests immediately.
• Flexible paid time off, generally around 25 days a year, plus 11 paid federal holidays.
• Up to 12 weeks of paid leave for eligible new birth, adoption or foster parents.
• Performance rewards: annual salary increase, annual performance bonus, spot bonuses and stock options.
• Business development and sales bonuses.
• Referral bonuses.
• $2,000 a year for professional development.
• $750 a year for tech-related purchases.
• A $100 annual swag budget for merchandise such as hoodies and hats.
• Flexible, remote-friendly work setup.