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Real World Evidence Epidemiology Jobs (NOW HIRING)

$186 - $345/hr

# Director, Real-World Evidence Data PlatformREQ-10084861Aug 14, 2026USAAvailable in:English ... Collaborate with analytics, epidemiology, biostatistics, medical, access, and other cross ...

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Real World Evidence Epidemiology information

What is real world evidence epidemiology?

Real World Evidence (RWE) Epidemiology is a field that uses data collected from real-world settings—such as electronic health records, insurance claims, patient registries, and digital health tools—to study the patterns, causes, and effects of health and disease in populations. Unlike traditional clinical trials, which are controlled and often have strict inclusion criteria, RWE epidemiology analyzes diverse, everyday patient experiences to inform healthcare decisions. This approach helps assess the effectiveness, safety, and value of medical interventions in routine clinical practice, supporting regulatory, clinical, and market access decisions.

How does a real world evidence epidemiologist typically collaborate with cross-functional teams in the healthcare industry?

Real World Evidence (RWE) Epidemiologists frequently work alongside data scientists, medical affairs, regulatory specialists, and clinical development teams to design and execute studies using real-world data. Collaboration often involves aligning on study objectives, data collection methods, and interpretation of results to ensure the evidence generated is robust and actionable for regulatory submissions, publication, or product development. Effective communication and project management skills are crucial, as these projects require input from diverse stakeholders and adherence to industry standards. This collaborative environment provides opportunities to learn from other disciplines while contributing epidemiological expertise to impactful healthcare decisions.

What are the key skills and qualifications needed to thrive as a real world evidence epidemiologist, and why are they important?

To thrive as a Real World Evidence Epidemiologist, you need a solid background in epidemiology, biostatistics, and data analysis, typically supported by an advanced degree such as an MPH, MS, or PhD in a related field. Proficiency in statistical software (e.g., SAS, R, or STATA), real-world data sources (like claims or EHR databases), and familiarity with regulatory requirements are essential. Strong communication, problem-solving, and cross-functional collaboration skills help translate complex data into actionable insights for stakeholders. These skills ensure robust, regulatory-compliant evidence generation that informs healthcare decisions and supports product value in real-world settings.

What is the difference between Real World Evidence Epidemiology vs Clinical Data Analyst?

AspectReal World Evidence EpidemiologyClinical Data Analyst
Required CredentialsMaster's or PhD in Epidemiology, Public Health, or related fieldBachelor's or Master's in Data Science, Biostatistics, or related field
Work EnvironmentResearch institutions, pharmaceutical companies, healthcare organizationsHospitals, research centers, healthcare IT companies
Industry UsageDesigning and analyzing real-world studies, observational researchManaging and analyzing clinical trial data, reporting

Real World Evidence Epidemiologists focus on studying health outcomes using observational data from real-world settings, while Clinical Data Analysts primarily handle clinical trial data analysis and reporting. Both roles require strong analytical skills but differ in their data sources and research focus.

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Infographic showing various Real World Evidence Epidemiology job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, 3% Contract, and 1% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution.

Associate Director, Real-World Evidence & Epidemiology

Natera

OR • On-site, Remote

Full-time

Posted 19 days ago


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

57th of 120 rated laboratories


Job description

POSITION SUMMARY:

We are seeking a Principal Clinical Scientist / Associate Director of Real-World Evidence & Epidemiology to drive observational evidence strategy for our Early Cancer Detection (ECD) portfolio. Population-scale liquid biopsy screening requires robust real-world evidence demonstrating clinical utility, clinical decision-making impact, and downstream patient outcomes. This ownership role uses real-world datasets to accelerate standard-of-care implementation across oncology diagnostics. Working with a builder mindset, you will partner across Clinical Science, Medical Affairs, Market Access, and Data Science to convert population-scale observational data into actionable clinical implementation strategies.

PRIMARY RESPONSIBILITIES:

Epidemiology and Observational Research Strategy

  • Lead the design, protocol development, and execution of prospective observational studies, registries, and retrospective database assessments across early cancer detection programs
  • Shape post-market evidence generation strategies by isolating critical clinical utility and implementation hurdles that can be resolved via real-world data assets
  • Translate clinical and market requirements into rigorous, practical study designs, specifying target populations, clinical endpoints, and analytic frameworks
  • Systematically identify and mitigate sources of bias, confounding factors, and missing data variance inherent in real-world healthcare datasets
  • Design protocols evaluating clinical utility across diverse populations, ensuring the data generated directly supports precision interventions for individual patients and families

Cross-Functional Scientific Leadership

  • Partner across Clinical Science, Medical Affairs, Product Management, and Market Access to prioritize evidence generation initiatives based on regulatory and clinical urgency
  • Collaborate with Biostatistics and Data Science to engineer statistical analysis plans, interpret data findings, and deliver clinical contextualization
  • Extract empirical evidence from early commercial and Laboratory Developed Test (LDT) cohorts to isolate adoption variables, diagnostic compliance, and real-world clinical workflows
  • Deliver real-world data assets that dismantle payer coverage barriers and ground product positioning strictly in clinical utility metrics

Evidence Dissemination and External Engagement

  • Convert complex epidemiological findings into clear, high-integrity scientific narratives for internal product governance and external healthcare stakeholders
  • Spearhead the development of peer-reviewed abstracts, posters, presentations, and core manuscripts for major oncology and diagnostic conferences
  • Engage with external clinical collaborators, investigators, and key opinion leaders (KOLs) to advance the platform base for early cancer detection

QUALIFICATIONS:

  • Advanced degree (PhD, MPH, MS, PharmD, or equivalent scientific credential) in epidemiology, health outcomes research, biostatistics, or a highly quantitative field
  • 7+ years of experience leading real-world evidence generation, observational clinical research, or HEOR portfolios within the life sciences industry
  • Documented experience executing observational studies across the entire asset lifecycle, from initial protocol drafting through statistical analysis and publication
  • Deep data competency across real-world data sources, including longitudinal medical claims, electronic health records (EHR), and clinical registries
  • Direct experience in oncology clinical trials, molecular diagnostics, or early cancer detection programs is preferred

KNOWLEDGE, SKILLS, AND ABILITIES:

  • Take full ownership of complex clinical portfolios as an autonomous strategist
  • Rigorous analytical skills with the ability to pressure-test study assumptions and ground major milestones entirely in data
  • Communicate with technical precision across matrixed lines to align R&D, commercial, medical, and lab operations functions
  • Strong ownership mindset with the capability to balance scientific rigor, speed, and trial resource constraints under tight timelines
  • Comfort with ambiguity and an evolving product surface as underlying genomic science advances

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