Syneos Health Careers 2026 | Real World Biostatistician Jobs (RWE Remote US

M.S. or Ph.D. in Biostatistics, Statistics, or Epidemiology

Are you searching for remote real-world biostatistician jobs in Canada or the USA, RWE observational study biostatistician careers at Syneos Health, or causal inference and claims data analytics vacancies? Global biopharmaceutical solutions CRO giant Syneos Health® is actively hiring for the position of Real World Biostatistician - RWE CMH Experience (Job : ).

In this full-time remote role, you will lead the design, statistical analysis, and interpretation of observational real-world evidence (RWE) studies using electronic medical records (EMR) and longitudinal claims data to inform clinical development, HEOR, regulatory strategy, and market access. Candidates holding a Master's or Ph.D. in Biostatistics, Statistics, or Epidemiology with 5+ years of RWD analytics experience and proficiency in SAS, R, Python, and SQL/OMOP data structures are eligible to apply.

• Job Title: Real World Biostatistician - RWE CMH Experience
• Job :
• Employment Type: Full-Time, Permanent
• Educational Background: M.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or related field (Ph.D. strongly preferred)
• Experience
  
  Required:
  
  ≥ 5 Years of experience in RWD/RWE analytics in industry or equivalent
• Technical Stack: SAS, R, Python, SQL logic, OMOP CDMs, ICD/NDC coding systems
• Methodologies: Causal Inference, Propensity Score Matching/Weighting, Trial Emulation, External Control Arms
• Date Posted: 23 July 2026

As a Real World Biostatistician at Syneos Health, your core duties will include:

• RWE Study Design & Execution: Design and execute real-world evidence (RWE) observational studies using EMR and claims databases; author statistical analysis plans (SAP), data specifications, and study protocols.
• Advanced Causal Inference: Develop and apply robust causal inference methodologies, including propensity score matching/weighting, GLM/GLMM, MMRM, survival analysis, and random forest models.
• Trial Emulation & External Controls: Implement target trial emulation frameworks, external control arm development, and statistical borrowing strategies.
• Healthcare Data Engineering: Perform statistical data extraction and cohort definitions using SQL logic, OMOP Common Data Models, and healthcare coding systems (ICD, NDC, SNOMED, RxNorm).
• Sample Size & Power Analysis: Conduct sample size estimation and statistical power calculations for observational, pragmatic, and hybrid study designs.
• Cross-Functional Partnership: Collaborate with HEOR, Market Access, Regulatory, and Clinical Development teams to translate complex analytical results into executive presentations and study reports.

Educational Eligibility:

• Master's (M.S.) or Doctorate (Ph.D.) degree in Biostatistics, Statistics, Epidemiology, or a related quantitative discipline (Ph.D. strongly preferred).

Required Experience & Technical

Competencies:

• Minimum 5 years of hands‑on experience in RWD/RWE biostatistics and observational study design.
• Demonstrated experience working with large‑scale EMR and longitudinal healthcare claims databases.
• Programming proficiency in at least one primary statistical language:
  SAS, R, or Python
  .
• Working knowledge of SQL logic for cohort extraction and OMOP data model structures.
• Proven mastery of causal inference methods, propensity score weighting/matching, and observational trial design.
• Prior experience with RWE CMH (Cochran‑Mantel‑Haenszel) methods and concept mapping (ICD SNOMED RxNorm).
• Familiarity with therapeutic areas such as Diabetes, Cardiovascular Disease, or Metabolic Disorders is preferred.
• Work for a premier global CRO that has contributed to 94% of all Novel FDA Approved Drugs and 95% of EMA Authorized Products over the past 5 years.
• Opportunity to shape RWE methodologies across 200+ studies and multi‑million patient datasets.
• Inclusive, purpose‑driven culture under the Driven to Deliver commitment.
• Comprehensive benefits package, continuous scientific development, and flexible remote work options across North America.

Yes, this position is a full-time remote/telecommute role open to candidates based in Canada or the United States.

An M.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or a related quantitative field is required (Ph.D. strongly preferred).

Proficiency in at least one statistical language (SAS, R, or Python) along with SQL logic for database querying is required.

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