Job description
NovaStat Analytics is seeking a results‑driven Senior Statistician to lead statistical strategy across product, clinical, and market research initiatives. You will design experiments, build predictive and causal models, and translate complex results into actionable business insights.
In this role, you’ll collaborate with data engineers, data scientists, product managers, and researchers to ensure rigorous methodology and robust inference. The ideal candidate has a strong foundation in statistics, experience with real‑world data, and a passion for communicating with non‑technical stakeholders.
Based in the San Francisco Bay Area, we offer competitive compensation, flexible work arrangements, and a culture of curiosity and impact.
Responsibility
- Lead design and analysis of experiments and observational studies to inform product and policy decisions.
- Develop and validate predictive, causal, and Bayesian models to drive business outcomes.
- Perform power analyses, sample size planning, data quality assessment, and measurement validation.
- Build and maintain reproducible analysis pipelines using R, Python, and version-controlled workflows.
- Communicate complex methods and results to non‑technical stakeholders through clear visuals and executive summaries.
- Collaborate with data engineers, data scientists, and product teams to ensure data availability and methodological rigor.
- Mentor junior statisticians and contribute to documentation, standards, and best practices.
Qualification
- PhD or MS in Statistics, Biostatistics, Mathematics, or a closely related field.
- 5+ years of applied statistics experience in industry or academia, with a track record of impactful projects.
- Proficiency in R and Python; experience with SAS, STATA, or SQL is a plus.
- Strong foundation in experimental design, hypothesis testing, regression, time-series, and causal inference.
- Experience with Bayesian methods and probabilistic programming is preferred.
- Excellent communication skills and the ability to explain methods to non‑technical audiences.
- Experience building data products or decision-support tools and creating data visualizations.
- Strong problem-solving mindset and ability to work independently in a fast-paced environment.