Principal Biostatistician Fsp, Rwe

**Job Level**:FSP Principal Biostatistician for Pharmaceutical RWE

**Location**:Home-based in Mexico

**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 directly with expert cross-functional sponsor teams. 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 statistical support for novel clinical research.

**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.

**Responsibilities**:
**Data Access and Collection**:

- Identify and access diverse RWD sources, such as electronic health records (EHRs), claims databases, patient registries, and other real-world data repositories.
- Collaborate with data vendors and healthcare organizations to ensure data quality, compliance, and accessibility.
- Develop robust data collection pipelines using advanced programming techniques to support study objectives.

**Data Analysis and Statistical Modeling**:

- Design and execute statistical analyses of RWD to generate RWE for clinical, regulatory, and commercial purposes.
- Leverage strong programming skills to develop, validate, and optimize analytical models and scripts for complex RWD datasets.
- Conduct comparative effectiveness research, health outcomes studies, and pharmacoeconomic analyses, addressing issues like confounding, bias, and missing data.

**Study Design and Protocol Development**:

- Collaborate with cross-functional teams to design RWE studies, including retrospective cohort studies, case-control studies, and pragmatic trials.
- Contribute to study protocols, statistical analysis plans (SAPs), and technical reports, ensuring programming components are clearly defined.
- Ensure studies align with regulatory standards (e.g., FDA, EMA) for RWE submissions.

**Reporting and Communication**:

- Prepare high-quality reports, manuscripts, and presentations summarizing RWE findings for internal stakeholders, regulatory authorities, and peer-reviewed publications.
- Use programming skills to create automated reporting tools and dynamic data visualizations for non-technical audiences.
- Provide strategic recommendations based on RWE to support drug development, market access, and lifecycle management.

**Compliance and Quality Assurance**:

- Demonstrate strong understanding of and Ensure compliance with regulatory guidelines (e.g., FDA 21st Century Cures Act, EMA RWE framework) and industry standards (e.g., ISPOR, ISPE), as applicable to statistics.
- Implement best practices for data integrity, reproducibility, and transparency through well-documented and efficient code.
- Perform quality control and validation of statistical and programming outputs.

**Qualifications**
- PhD in Statistics, Biostatistics, or related field with 5+ years industry experience.
- MS in Statistics, Biostatistics, or related field with 7+ years of industry experience.
- Proven expertise in RWD/RWE studies, with hands-on experience analyzing EHRs, claims data, registries, or other real-world data sources.
- Experience with different study designs, protocol development, and statistical analysis plan writing
- Demonstrated track record of supporting regulatory submissions (e.g., FDA, EMA) using RWE.
- Excellent problem-solving and critical-thinking skills.
- Strong communication and collaboration abilities to work with cross-functional teams and external partners.
- Ability to manage multiple projects and meet deadlines in a fast-paced environment.
- Experience with statistical modelling of clinical data and statistical inference
- Strong Programming Skills: Advanced proficiency in statistical programming languages such as R, Python, or SAS for data manipulation, statistical analysis, and automation.
- Experience with database querying (e.g., SQL) and managing large, complex datasets.
- Familiarity with data visualization tools (e.g., Tableau, Power BI, or R Shiny) to create impactful presentations of RWE findings.
- Knowledge of version control systems (e.g., Git) and reproducible research practices.
- Based in a time zone within the United States or Europe