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Why this grade This listing scored 45/100, which is a D. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
-10 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Full-Time Senior Data Science & Analytics
As a Principal Analyst, Data Integration, you will own the end-to-end process of evaluating, scoping, and onboarding new data sources into H1's platform. This is a senior IC role at the intersection of data, engineering, and product — the connective tissue between raw data acquisition and what ultimately ships to clients. You will work across Data & Research, Engineering, and Product to define what a new source is, how it maps to H1's schemas, what it can realistically deliver, and what it can't. You will also work directly with client-facing teams to gather requirements before integration decisions are made, translating commercial needs into data specs and data constraints back into product expectations.
You will:
- Lead structured evaluation of new data sources from scratch — assessing schema, coverage, freshness, legal constraints, and fit against H1's product needs before any engineering work begins
- Own field mapping from source to H1's bronze/silver/gold layers, producing data dictionaries, entity definitions, and structural guidance for downstream teams
- Partner with engineering and Data Lake to define ingestion requirements, entity resolution rules, and refresh cadences for new sources
- Gather requirements from client-facing teams and translate them into integration specifications; serve as the authoritative voice on what a new source can and cannot deliver before product commitments are made
- Shepherd each source end-to-end: scoping → QA → entity matching → product launch, including product QA and communicating source capabilities and limitations to product and enablement partners
- Work with the Insights team to develop new taxonomies and QA mechanisms for novel data types
- Define acceptance criteria and lead QA validation including field-level fill rates, count comparisons, and cycle-over-cycle anomaly detection
- Investigate and resolve data quality issues post-integration, coordinating with DART and engineering as needed
- Hand off to the maintaining team with complete mapping documentation; you own onboarding, not ongoing maintenance
- Produce and maintain documentation other people actually use — across scoping assessments, field mapping specs, and post-mortems
- Demonstrated end-to-end ownership of data integrations built from scratch — scoping, field mapping, QA, and handoff — with documentation to show for it
- Healthcare or life sciences domain context required; ability to ramp on new datasets and source types each quarter without needing deep subject matter expertise upfront
- Analytical fluency to assess data quality; hands-on experience with tools such as VBA, R, or SPSS; SQL a plus but not a primary requirement
- Familiarity with data lake architectures (bronze/silver/gold or equivalent) and how raw data moves through normalization and entity resolution to a product-ready state
- Experience gathering requirements from client-facing stakeholders and translating them into data or product specifications
- Experience at a B2B data company where you understood how external clients consumed your data and where client retention drove decisions
- AWS infrastructure familiarity (Athena, S3, Glue) at a query and inspection level preferred
- Comfort working in Jira or Monday in a ticket-based workflow
- Exceptional written communication — your documentation is legible, maintained, and actually used COMPENSATIONThis role pays $145,000 to $170,000 per year, based on experience, in addition to equity. Anticipated role close date: 08/25/2026 H1 OFFERS- Full suite of health insurance options, in addition to generous paid time off- Pre-planned company-wide wellness holidays- Retirement options- Health & charitable donation stipends- Impactful Business Resource Groups- Flexible work hours & the opportunity to work from anywhere- The opportunity to work with leading biotech and life sciences companies in an innovative industry with a mission to improve healthcare around the globe H1 is proud to be an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and teammates. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, ancestry, national origin, religion, disability, sex (including pregnancy), age, gender, gender identity, sexual orientation, marital status, veteran status, or any other characteristic protected by law. H1 is committed to working with and providing access and reasonable accommodation to applicants with mental and/or physical disabilities. If you require an accommodation, please reach out to your recruiter once you've begun the interview process. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.
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Where this listing came from
- 28 Jul 2026 Jobicy first sighting
Seen on 1 board over 63 days. The employer edited the description 2× since we first recorded it.