Job description
NovaMetrics Analytics is seeking a talented Senior Statistician to join our fast-growing analytics team in San Francisco. You will design, implement, and interpret advanced statistical analyses to guide product strategy, policy decisions, and performance optimization.
We value rigorous methodology, clear communication, and collaborative problem solving. This role blends applied statistics, experimental design, data visualization, and stakeholder storytelling to turn data into measurable business impact.
Responsibility
- Design and execute complex statistical analyses on large, multi-source datasets to inform product and business decisions.
- Lead experiments and A/B testing programs, including sample size calculations, power analyses, and result interpretation.
- Develop and validate predictive models (e.g., regression, time-series, survival, or Bayesian models) to forecast key metrics.
- Collaborate with data engineers to ensure data quality, reproducibility, and scalable analytic pipelines.
- Communicate insights to non-technical stakeholders through clear visuals and storytelling.
- Mentor junior analysts, review code and analyses, and promote best practices in statistics and data science.
- Maintain rigorous documentation and contribute to reproducible research practices and model governance.
Qualification
- Master’s or PhD in Statistics, Biostatistics, Mathematics, or a related quantitative field.
- Minimum 4 years of applied statistical analysis experience in industry or academia.
- Proficiency in R and Python; experience with SQL and data visualization tools (Tableau, Power BI, or similar).
- Strong knowledge of experimental design, hypothesis testing, and regression modeling; experience with time-series and Bayesian methods is a plus.
- Excellent communication skills with the ability to present complex results to non-technical audiences.
- Ability to work cross-functionally, manage multiple projects, and deliver high-quality analyses on tight timelines.
- Experience with cloud data platforms (e.g., AWS) and version control (Git) is preferred.