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

Real World Biostatistician - RWE CMH experience (hiring in Canada and US) 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. Discover what your 25,000 future colleagues already know: Why Syneos Health • We 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.  Job Responsibilities Job Description Biostatistician – Real-World Evidence (RWE)   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 RWE 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 (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:  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 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  RWE CMH Experience Preferred Qualifications   Ph.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 RWD  Demonstrated ability to work across multiple therapeutic areas (TAs) in a fast-paced environment  Strong communication and stakeholder engagement skills  Advanced (nice-to-have, not always required)   Build reusable cohort pipelines  Optimize queries for large-scale databases  Work across multiple CDMs (OMOP, Sentinel, PCORnet)  Core Competencies   Analytical rigor and methodological depth  Cross-functional collaboration  Ability to operate with agility across diverse projects and therapeutic areas  Clear and effective scientific communication  Get to know Syneos Health Over the past 5 years, we have worked with 94% of all Novel FDA Approved Drugs, 95% of EMA Authorized Products and over 200 Studies across 73,000 Sites and 675,000+ Trial patients. 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 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 des