Job description
At NovaStat Analytics, we help organizations unlock value from data through rigorous statistics and data science. We are seeking a Senior Applied Statistician to lead high-impact projects and mentor a growing analytics team.
In this role you will collaborate with cross-functional teams to design studies, build predictive models, and translate results into actionable business strategies.
Responsibility
- Lead end-to-end statistical analyses for complex datasets across healthcare, finance, and consumer analytics.
- Design and execute experiments, A/B tests, and power analyses to inform product and business decisions.
- Develop and validate advanced models (GLMs, mixed effects, survival analysis, Bayesian methods) and ensure robust inference.
- Clean, transform, and explore large-scale data; implement reproducible data pipelines and documentation.
- Collaborate with product, engineering, and business stakeholders to translate insights into actionable recommendations.
- Communicate complex statistical results to non-technical audiences and create compelling visualizations.
- Mentor junior statisticians and contribute to methodological development and best practices.
- Ensure adherence to data governance, privacy, and regulatory requirements across projects.
Qualification
- MS or PhD in Statistics, Biostatistics, or a closely related field; 3+ years of applied statistics experience; or BS with 5+ years of relevant experience.
- Strong modeling expertise in GLMs, mixed effects, survival analysis, and Bayesian methods.
- Proficiency in R; Python; SAS; SQL; experience with data visualization tools (Tableau/Power BI) is a plus.
- Demonstrated experience in experimental design and A/B testing with solid power analysis.
- Experience with healthcare or finance data is a plus; excellent communication and storytelling skills.
- Proven ability to translate complex analyses into actionable business insights and manage multiple priorities.
- Strong knowledge of reproducible research practices and version control (Git).