Job description
NovaStat Analytics is seeking a highly skilled Applied Statistician to lead data-driven decision making across product, operations, and research teams. The ideal candidate will design experiments, build predictive models, and translate complex analyses into actionable insights for senior stakeholders. This role blends rigorous statistical methodology with practical business impact in a fast-paced environment.
As a member of our methodological excellence group, you will influence strategic decisions, ensure reproducibility, and mentor junior analysts. The position offers advanced tooling, collaboration with cross-functional teams, and opportunities for career growth in a dynamic, data-driven company.
Responsibility
- Lead design and execution of applied statistics projects from problem framing to insight delivery.
- Develop and validate predictive models using regression, time-series, and Bayesian methods.
- Collaborate with product, engineering, and research teams to translate analytics into actionable strategies.
- Ensure rigorous experimental design, A/B testing, and causal inference where appropriate.
- Mentor junior analysts, promote reproducible research practices, and contribute to code reviews.
- Present findings to executives and cross-functional stakeholders with clear, data-driven storytelling.
- Maintain documentation and data governance aligned with regulatory and quality standards.
Qualification
- MS or PhD in Statistics, Biostatistics, Applied Mathematics, or a closely related field.
- 5+ years of applied statistics experience in industry or academia.
- Strong proficiency in R and Python; experience with SAS or STATA a plus.
- Expertise in experimental design, causal inference, regression models, and time-series analysis.
- Experience with Bayesian methods and probabilistic programming is a plus.
- Excellent communication and ability to translate complex results for non-technical stakeholders.
- Proven track record of delivering impact through data-driven decisions.
- Familiarity with data visualization and reporting tools; strong SQL skills.