Real World Biostatistician - RWA CMH experience (hiring in Canada and US)

Location: Remote, ON, Canada

Job ID: 25112122

Description: Real World Biostatistician - RWE Cardiometabolic experience (hiring in Canada and US) PhD mandatory Syneos Health® is a leading fully-integrated life sciences services organization built to accelerate customer success. We partner with innovators at every point across the drug development and commercialization continuum, helping them navigate complexity, anticipate change and accelerate progress. Our Clinical Solutions team members act with a drug development mindset, applying their years of experience and deep expertise to truly understand customer needs and represent those in the solutions we shape. Whether you join us in a Functional Service Provider partnership or a Full-Service environment, you’ll collaborate with passionate problem solvers, innovating as a team to help our customers achieve their goals. We are agile and driven to deliver – for one another, our customers, and, most importantly, for those in need. Why Syneos HealthWe are passionate about developing our people, through career development and progression; supportive and engaged line management; technical and therapeutic area training; peer recognition and total rewards program. We are committed to building an inclusive culture – where you can authentically be yourself. Central to this is our purpose – Driven to Deliver – which captures the passion of our colleagues to show up each day and shape solutions that have the ability to dramatically impact someone’s life. We are continuously building the company we all want to work for and our customers want to work with. Why? Because we know that when we bring together smart colleagues from across the world, we can shape the future of healthcare, driving impact for customers and defining the pace of patient progress. No matter what your role is, you’ll take the initiative and challenge the status quo with us in a highly competitive and ever-changing environment. Learn more about Syneos Health. http://www.syneoshealth.com

Job Responsibilities: Biostatistician – Real-World Evidence (RWA)

Role Overview: We are seeking a biostatistician with strong experience in real-world data (RWD) with observational study design and safety study experience in addition to RWA CMH experience. This role will support evidence generation across multiple therapeutic areas. This role will focus on the design, analysis, and interpretation of observational studies using EMR and claims data to inform: clinical development, HEOR, regulatory strategy, and market access.

Key Responsibilities: Design and execute real-world evidence (RWA) studies using EMR and claims data; conducting data specs, SAP and protocol with key research objectives Develop and apply robust statistical methodologies, including Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM; survival analysis; random forest) Trial emulation frameworks External control arm development and borrowing strategies Perform data analysis using healthcare coding systems (e.g., ICD, NDC) Conduct sample size estimation and power calculations for observational and hybrid study designs Collaborate cross-functionally with stakeholders across: HEOR, Market Access, Regulatory, Clinical Development Translate complex analytical results into clear, actionable insights, e.g. powerpoint or study report for decision-making Support methodological innovation in RWE, including integration of machine learning approaches where appropriate

Required Qualifications: M.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or related field ≥5 years of experience in RWA/RWD analytics (industry or equivalent) Strong experience with EMR and/or claims data Proficiency in healthcare coding systems (e.g., ICD, NDC) Programming expertise in at least one of: SAS, R, or Python Working knowledge with SQL logic and OMOP data structures Solid understanding of: Causal inference methods, Observational study design, Sample size and power considerations Some examples: Independently write cohort definitions in SQL logic; Debug data issues e.g., time zero alignment, exposure gaps; Understand concept mapping (ICD - SNOMED - RxNorm); Translate statistical estimand -> censoring rule and data extraction logic RWE CMH Experience

Preferred Qualifications: Ph. D. strongly preferred Experience in one or more therapeutic areas:

• Diabetes
• Cardiovascular disease
• Metabolic disorders

Additional Information: Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities. Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description. The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above. Further, nothing contained herein should be construed to create an employment contract. Occasionally, required skills/experiences for jobs are expressed in brief terms. Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees. The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.

Job Description: Summary Biostatistician – Real-World Data (RWA)

Role Overview: We are seeking a biostatistician with strong experience in real-world data (RWD), observational study design, and RWE CMH to support evidence generation across multiple therapeutic areas. This role will focus on the design, analysis, and interpretation of observational studies using EMR and claims data to inform: clinical development, HEOR, regulatory strategy, and market access.

Key Responsibilities: Design and execute real-world evidence (RWE) studies using EMR and claims data; Conducting data specs, SAP and protocol with key research objectives Develop and apply robust statistical methodologies, including:

• Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM; survival analysis; random forest)
• Trial emulation frameworks
• External control arm development and borrowing strategies
• Perform data analysis using healthcare coding systems (e.g., ICD, NDC)
• Conduct sample size estimation and power calculations for observational and hybrid study designs
• Collaborate cross-functionally with stakeholders across:
• HEORMarket Access
• RegulatoryClinical Development
• Translate complex analytical results into clear, actionable insights, e.g. powerpoint or study report for decision-making
• Support methodological innovation in RWE, including integration of machine learning approaches where appropriate
• ShapeRequired QualificationsM.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or related field≥5 years of experience in RWD/RWE analytics (industry or equivalent)
• Strong experience with EMR and/or claims data
• Proficiency in healthcare coding systems (e.g., ICD, NDC)
• Programming expertise in at least one of: SAS, R, or Python
• Working knowledge with SQL logic and OMOP data structures
• Solid understanding of:
• Causal inference methods
• Observational study design
• Sample size and power considerations
• Some examples: Independently write cohort definitions in SQL logic; Debug data issues e.g., time zero alignment, exposure gaps; Understand concept mapping (ICD - SNOMED - RxNorm); Translate statistical estimand -> censoring rule and data extraction logic
• ShapePreferred QualificationsPh.
• D. strongly preferred
• Experience in one or more therapeutic areas:
• Diabetes
• Cardiovascular disease
• Metabolic disorders
• Familiarity with:
• Trial emulation methodologies
• External control borrowing / hybrid designs
• Basic machine learning methods applied to RWDDemonstrated ability to work across multiple therapeutic areas (TAs) in a fast-paced environment
• Strong communication and stakeholder engagement skillsRWE CMH Experience
• Advanced (nice-to-have, not always required)
• Build reusable cohort pipelines
• Optimize queries for large-scale databases
• Work across multiple CDMs (OMOP, Sentinel, PCORnet)
• ShapeCore CompetenciesAnalytical rigor and methodological depth
• Cross-functional collaboration
• Ability to operate with agility across diverse projects and therapeutic areas
• Clear and effective scientific communication