---
title: 'Principal Data Scientist at Pedestal Health'
canonical: 'https://feeny.ai/job/principal-data-scientist-pedestal-health-research-triangle-park-zgwh50nmz6gp'
type: 'job'
last_seen: '2026-09-14'
---

# Principal Data Scientist at Pedestal Health

- **Company:** Pedestal Health
- **Location:** Research Triangle Park, NC
- **Posted:** 2026-09-10
- **Last confirmed live:** 2026-09-14
- **Apply:** https://job-boards.greenhouse.io/pedestalhealth/jobs/5420751008

## Job description

## The Role

We are seeking a Principal Data Scientist to join Pedestal Health's Quantitative Sciences (QS) organization. In this role, you will build the infrastructure and methods that make AI-assisted analytics and real-world data quality work fast, scalable, and genuinely trustworthy.

Your work will span two connected areas. The first is AI-enabled analytics: building and maintaining AI tooling and workflows that let our team identify cohorts, review analysis code, and carry out recurring analytic work faster and more consistently. The second is AI-enabled data quality: designing automated and agentic approaches that scale across schemas, sites, and data refreshes, and that surface issues before they reach an analysis or a client.

This is a role about building capability, not about producing analyses. You will design, build, and scale the internal tools that change how our teams work with real-world data — and you will own them as products, with users, versions, quality standards, and a roadmap. This is a hands-on role that combines individual technical contribution with technical leadership, including mentorship and review of other data scientists' work. You will partner closely with Product, Engineering, Medical, and Commercial teams, and report to the Head of Quantitative Sciences.

## What You'll Do

Build and Scale Internal Tooling

You will make AI a dependable part of how our analytic work gets done, not an occasional shortcut.

- Build, maintain, and improve AI-powered tooling that lets the team generate commercial cohort counts and conduct feasibility reliably and repeatably
- Extend the same approach to other recurring analytic work, including generating and reviewing analysis code, and supporting protocol and analysis plan development
- Gather requirements from the internal teams who depend on these tools, treat them as users, and iterate on real feedback rather than assumed needs
- Own what keeps this tooling trustworthy over time (how it is tested against known-correct results, how updates are validated before release, and how performance is monitored as the underlying data evolves), and where human review remains mandatory
- Scale adoption across the team through documentation, training, onboarding, and hands-on enablement
- Help define the guardrails for AI use in client-facing work: what data may be used, how outputs are reviewed and by whom, and how provenance is recorded

AI-Enabled Data Quality

You will design the infrastructure that tells us whether our data is trustworthy, before anyone else has to find out.

- Rethink how our data quality checks are built and run, so that assessing a new source or a refreshed schema no longer means redoing the work each time
- Move quality assessment beyond manual review and spreadsheet outputs, toward an automated approach with a durable record of what was checked, what was found, and how it was resolved
- Determine where AI and agentic approaches genuinely add leverage in this work, and where deterministic, reproducible checking should remain the foundation
- Define how we will know the system is working, including whether the people who receive quality signals continue to trust them and act on them
- Partner with Engineering on pipeline integration, orchestration, and monitoring

Cross-Functional Collaboration and Team Development

You will connect data science to the teams that build, sell, and deliver on top of it.

- Partner closely with Product, Engineering, Medical Science, Clinical Operations, and Commercial teams
- Advocate effectively for the quality and validation work that AI-assisted products require, including in roadmap and prioritization discussions
- Keep pace with developments in AI tooling and methods, and actively push what proves useful into our standards, training, and tooling
- Provide technical oversight, code review, and mentorship to other data scientists, and own the standards their work is measured against
- Help grow the data science group as it expands

## What You'll Bring

- MS or PhD in data science, statistics, computer science, computational biology, or a related quantitative field; equivalent practical experience will be considered
- Experience working with real-world healthcare data — EHR, claims, or registry — including direct familiarity with its structural and quality challenges
- A track record of building internal tools, platforms, or analytic products used by other people, and owning them through multiple versions — not solely a record of delivering analyses
- Strong programming ability in Python and SQL, with experience in a cloud data warehouse environment such as Snowflake
- Demonstrated ownership of a data quality, testing, or observability system end to end, not only authoring individual checks
- Practical experience building with large language models beyond prototyping, including prompt and workflow design and a clear point of view on how to evaluate whether an LLM-based system is actually working
- Comfort working in raw, messy, poorly documented source data, and the curiosity and persistence to figure out what it actually contains
- Experience working cross-functionally with product and engineering partners, and the ability to hold a technical line constructively when priorities compete
- Clear written and verbal communication, including the ability to explain a method's limitations as readily as its results
- Interest in growing into technical leadership, including mentoring and reviewing the work of other data scientists

## What we offer you

- Hybrid work — 3 days/week in our brand-new office!
- Comprehensive health, dental, and vision for you and your family
- 401(k) with company match
- Generous PTO and company holidays
- Paid parental leave

Hybrid role: Located in Research Triangle Park, North Carolina

If you are ready to be part of a team where your work truly matters—where your expertise is valued, your growth is supported, and your contributions help shape the future of healthcare—Pedestal Health is the place for you. We’re building something meaningful together, and we’d love for you to be a part of it.

Pedestal Health is an equal opportunity employer and seeks candidates from diverse backgrounds and abilities.

## About Pedestal Health

## Company Overview
- **One-liner**: Pedestal Health is an integrated evidence generation partner for life sciences organizations, building continuous, longitudinal patient cohorts to support drug development, regulatory decisions, and clinical care.
- **Entity Type**: Private (Part of Highlander Health, a venture-backed company co-founded by Amy Abernethy and Brad Hirsch)
- **Headquarters**: Durham, North Carolina, USA
- **Founded**: The company emerged from the rebranding of Target RWE and NoviSci, announced in May 2026. Target RWE was founded earlier; the current entity is the result of that merger.
- **Founders**: Co-CEOs: Amy Abernethy, MD, PhD, and Brad Hirsch, MD

## Core Business
- **Primary industry/industries**: Healthcare Technology, Real-World Evidence (RWE), Clinical Research, Life Sciences Data & Analytics
- **Target customers**: Pharmaceutical and biotech companies, health systems, payers, and regulatory bodies (FDA/EMA).
- **Mission or purpose statement**: To build a modern evidence-generation engine that reduces treatment access time by 50% through continuous evidence and personalized care, moving from episodic, start-from-scratch clinical studies to an infrastructure that compounds over time.

## Products & Services
- **Longitudinal Real-World Data Cohorts**: Deeply phenotyped, disease-specific patient datasets (e.g., hepatology, dermatology, gastroenterology) built directly from clinical practice, continuously queried for safety, effectiveness, and regulatory studies.
- **Regulatory-Grade Evidence Generation**: Full-service design and execution of externally controlled trials, prospective interventional studies, registries, and traditional real-world evidence studies for submission to FDA/EMA/HTA bodies.
- **Headwater Science (Sister Company)**: A methodological and analytical engine offering deep expertise in causal inference, comparative effectiveness, healthcare utilization, and regulatory-grade analytical software. This is a separate but closely integrated entity within Highlander Health.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Formed from the merger of two established companies (Target RWE and NoviSci) with strong existing revenue and partnerships; backed by Highlander Health, which is focused on evidence generation innovation.
- **Notable Investors/Partners**: Highlander Health (the lead investor and parent company). Key health system partnerships are highlighted (e.g., University of North Carolina).
- **Growth Signals**: Rebranding and strategic merger in May 2026 signals significant capital and strategic ambition. The company is actively hiring across multiple roles (engineering, data science, delivery, finance). Leadership includes former FDA Deputy Commissioner (Amy Abernethy) and founder of a successful clinical trial technology company (Brad Hirsch).

## Competitive Advantages
- **Continuous Evidence Infrastructure**: Unlike traditional CROs or data providers, Pedestal builds **continuous** cohorts that compound over time, avoiding the "start from scratch" model for every new study.
- **Deep Clinical Domanin Expertise**: Deepest footprint in hepatology, dermatology, and gastroenterology with pre-existing, deeply phenotyped patient populations and long-standing health system relationships.
- **Regulatory & C-Suite Credibility**: Leadership team with unparalleled experience (former FDA Principal Deputy Commissioner, founders of successful healthcare tech companies, top clinical researchers). This translates into regulatory-grade outputs trusted by agencies.
- **Integrated Methodological Engine (Headwater Science)**: Built-in access to world-class causal inference and data science expertise for complex analytical challenges, a significant moat against generalist competitors.
- **Health System Embeddedness**: Data is sourced directly from clinical practice, offering a richer, more longitudinal picture of patient journeys than claims data alone.

## Strategic Focus
- **Current priorities**: Expanding into new therapeutic areas beyond their core hepatology, dermatology, and GI strongholds. Scaling the "continuous evidence system" model across more biopharma partners. Integrating more deeply with health system IT for seamless data flow.
- **Direction for growth**: Becoming the "evidence infrastructure" for the life sciences industry, moving from project-based work to platform-based, recurring partnerships. Focus on solving the most complex, high-stakes regulatory and access questions.

## Why Work Here
- **Culture**: The company emphasizes passion, dedication, and use of patient data to shift the healthcare paradigm. They highlight "diverse and innovative perspectives" as core to their cutting-edge approach.
- **Remote/Hybrid Policy**: **Hybrid work** is explicitly offered as a benefit.
- **Notable Perks & Benefits**:
    - Competitive Health Insurance
    - **Paid Parental Leave**
    - Professional Development Courses
    - Employee Recognition Programs
    - Paid Holidays & Floating Holidays
    - **401(k) with Company Match & Immediate Vesting**
    - Paid Time Off
- **Engineering/Data Science Culture**: At the intersection of clinical research, data science, and regulatory technology. The work directly impacts drug development timelines and patient access. The team includes world-class biostatisticians, epidemiologists, data engineers, and product managers. For those passionate about data for social impact in health, this is a mission-driven, fast-paced environment backed by deep expertise.

## Sources
1. [Pedestal Health Official Website](https://www.pedestalhealth.com/)
2. [About Us / Leadership](https://www.pedestalhealth.com/about/)
3. [Careers Page (Greenhouse)](https://job-boards.greenhouse.io/pedestalhealth)
4. [Pedestal Health Careers / Benefits](https://www.pedestalhealth.com/careers/)
5. [Yahoo Finance: Target RWE and NoviSci Rebrand as Pedestal Health and Headwater Science](https://finance.yahoo.com/sectors/healthcare/articles/target-rwe-novisci-rebrand-pedestal-110000567.html)

## Other roles at Pedestal Health

- [Senior Clinical Research Associate](https://feeny.ai/job/senior-clinical-research-associate-pedestal-health-research-triangle-park-mms5e1bjft8k) — Research Triangle Park, NC
- [Study Start-up and Regulatory Manager](https://feeny.ai/job/study-start-up-and-regulatory-manager-pedestal-health-research-triangle-park-bvrc351c41c1) — Research Triangle Park, NC
- [Director Data Management](https://feeny.ai/job/director-data-management-pedestal-health-united-states-em1ws5k0pbyt) — United States
- [Data Engineer](https://feeny.ai/job/data-engineer-pedestal-health-research-triangle-park-ydmccp5n5c8e) — Research Triangle Park, NC
- [Cloud Security Engineer (AWS)](https://feeny.ai/job/cloud-security-engineer-aws-pedestal-health-research-triangle-park-qy1h836f1dex) — Research Triangle Park, NC
- [Senior AI/ML Engineer](https://feeny.ai/job/senior-ai-ml-engineer-pedestal-health-united-states-4z1bqhq3njgq) — United States
- [Principal Data Scientist](https://feeny.ai/job/principal-data-scientist-marshmallow-london-s5yzrs5hcnwz) — London, United Kingdom
- [Principal Data Scientist](https://feeny.ai/job/principal-data-scientist-faculty-united-kingdom-dv6xt7n54s2x) — United Kingdom
- [Principal Data Scientist](https://feeny.ai/job/principal-data-scientist-flagship-pioneering-inc-cambridge-tt225vq43cdw) — Cambridge, MA
- [Principal Data Scientist](https://feeny.ai/job/principal-data-scientist-g-p-india-em3wmfmzkrcc) — India