Manager, Clinical Data Science & Data Products

Job Description

Job DescriptionManager, Clinical Data Science & Data Products (Applied AI)

Location: U.S. Remote (with optional hybrid in a major metro)
Type: Full-time
Level: Mid–Senior (people manager / player-coach)

Beacon Talent is conducting a confidential search for a venture-backed company building an applied AI + data platform used in regulated healthcare environments. The company helps technical teams access, standardize, and validate complex clinical datasets so they can develop and evaluate AI responsibly.

The Role

You will lead a small team responsible for turning raw clinical data into analysis- and model-ready datasets that are reliable, well-documented, and usable by both internal teams and external partners. This role blends people leadership, hands-on technical work, and program ownership across multiple concurrent data initiatives.

What You’ll Do

Lead delivery of clinical data products

• Own dataset buildouts end-to-end: intake → profiling → transformation → validation → packaging → release.

• Translate ambiguous requests into clear scopes, success criteria, milestones, and delivery plans.

Manage and grow a high-performing team

• Coach, develop, and support a team of data scientists/analysts; set expectations and maintain quality bars.

• Hire and onboard as the team scales; establish repeatable workflows (reviews, documentation standards, runbooks).

Build scalable, harmonized data foundations

• Design and maintain curated clinical data layers that support repeatable analytics and ML workflows (not one-off extracts).

• Partner with Engineering to productionize pipelines and implement safeguards around quality, lineage, and access controls.

Work across diverse healthcare sources

• Investigate and operationalize new sources as they come online (e.g., EHR extracts, claims-like feeds, clinical text, imaging metadata, device/monitoring outputs).

• Ensure data integrity through profiling, anomaly detection, reconciliation, and rigorous QA.

Be a technical partner to customer-facing teams

• Support stakeholder communication on delivery status, limitations, and data interpretation in a clear, accessible way.

• Contribute to playbooks and reusable artifacts that make delivery faster over time.

What Success Looks Like

• Datasets ship on time with predictable quality, strong documentation, and minimal rework.

• Your team runs a consistent process for intake, transformation, validation, and release.

• Internal stakeholders trust the data layers as “source of truth” for downstream analysis and product development.

Qualifications

Required

• Experience leading teams (formal or informal), with strong project management instincts in technical environments.

• Deep hands-on experience with healthcare data (EHR, claims, registries, clinical research datasets, etc.).

• Strong proficiency in SQL and at least one analytics language (typically Python).

• Demonstrated ability to communicate both detailed technical tradeoffs and executive-level summaries.

• Strong writing/documentation skills and a quality-first mindset in regulated data contexts.

Nice to have

• Familiarity with common health data standards/terminologies (e.g., FHIR/HL7 concepts, ICD/CPT/LOINC/SNOMED-style vocabularies).

• Experience with modern transformation tooling (e.g., dbt-like workflows), version control, and cloud data stacks.

• Exposure to clinical NLP, imaging (DICOM ecosystems), or common data models (e.g., OMOP-style structures).

• Startup/early-stage experience where priorities shift and you build process as you go.

Working Style & Logistics

• Fast-paced, iterative environment; emphasis on learning, experimentation, and continuous improvement.

• Occasional in-person team gatherings (typically quarterly).

Compensation

Competitive base + equity + benefits (details shared during the process).