Principal Biostatistician FSP, RWE
Job Level: FSP Principal Biostatistician for RWE Research Location: Home-based in the U.S. or Canada Why DSSS? Data Sciences Staffing Solutions, DSSS, is a unit within IQVIA that provides our sponsors with fully embedded resources through a Functional Service Provider (FSP) partnership. This means you get all the benefits of working for an industry leading global CRO while collaborating with expert sponsor teams. These sponsor clients include world class pharmaceutical and biotech companies offering you unique opportunities to influence the future of medicine and advance therapies to market. Job Summary: The Principal Biostatistician is responsible for providing full range statistical support for drug development based on real world evidence (RWE). Additional Benefits:
- Home-based remote working opportunities
- Work/life balance as well as flexible schedules.
- Collaborating with motivated, high-performance, statistical and research teams
- Technical training and tailored development curriculum
- Research opportunities that match your unique skillset
- Promising career trajectory
- Job stability: long-term engagements and re-deployment opportunities
- Focus on bringing new therapies to market rather than project budgets and change orders.
- Experience with regulatory submissions.
- Engaging, fast-paced environment.
- Good work-life balance.
Job Requirements:
- Collaborate with multi-disciplinary project teams to establish project goals and timelines.
- Serves as statistical lead and represents Biometrics on health outcomes and epidemiology studies.
- Serves as subject matter expert for RWE/HEOR/HTA research design, methodologies, data sources, analytic techniques, and reporting.
- Writes statistical analysis plans.
- Provides strategic and tactical support for cross-functional RWE development for regulators, payers, and clinicians.
- Leverages administrative claims, electronic medical records, registries, or other real-world data and recommends optimal analysis.
- Selects and implements appropriate analytical methods including statistical models or machine learning models to align with overall business objectives.
- Develops high quality study protocols, statistical analysis plans, study reports, and other study documents.
- Identifies innovation opportunities for the use of RWD.
- Establishes effective communication with various internal stakeholders to understand and support the strategy for when and how to use RWD.
- Commitment to maintaining the highest standards of data accuracy and integrity by implementing rigorous quality control processes throughout the data handling and analysis phases.
- Demonstrated ability to quickly adapt to new requirements and efficiently handle ad-hoc requests.
Required Knowledge, Skills, and Abilities:
- In-depth knowledge of RWE databases, including large administrative claims data, EMR, disease registries, and clinical trial data.
- Demonstrated ability in evaluation and development of RWE from conceptualization through application.
- Familiarity with LOINC codes, reimbursement and lab data interpretation, and ability to implement surrogate variable algorithms (e.g., phenotype definitions, proxies for clinical endpoints)
- Ability to execute statistical analysis plans using advanced programming techniques to perform detailed and complex analyses relevant to real-world evidence.
- Ability to effectively interpret and communicate research results to internal and external audiences.
- Understanding of ICH GCP and E9 as well as general knowledge of industry practices and standard
- Knowledge of global regulatory and HTA requirements for RWE
- Excellent organizational skills and proven ability to effectively lead multiple projects to successful completion.
- SME-level proficiency in SAS programming tailored to handle complex inclusion and exclusion criteria, conduct propensity score matching, and develop outcome metrics.
Required Education and Experience: (Minimal acceptable level of education, work experience, and competency)
- Ph.D. in Statistics, Biostatistics, or related field with 5+ years of industry experience.
- Experience leading secondary data analysis, including medical claims, electronic medical records, chart reviews, and registries.
- Solid hands-on experience as Project statistician with real-world data, including EMR/EHR and claims datasets (e.g., Humedica, Optum, MarketScan, CMS, Komodo, Truveta, TrinetX, etc.)
- Fluency in LOA, mock TFLs, protocol and SAP
- Experience in cost analysis and healthcare resource utilization (HCRU) evaluation using RWD
- Experience with CDISC A
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