Job description
NovaAnalytics Labs is seeking a Senior Applied Statistician to join our growing data science team in New York. You will design and execute rigorous statistical analyses to inform product strategy, pricing, and customer insights. The ideal candidate excels at translating complex data into actionable recommendations and communicating findings to cross-functional stakeholders.
This role blends theoretical statistics with practical applications, including experimental design, regression modeling, time-series analysis, and Bayesian methods, with a focus on delivering measurable business impact.
Responsibility
- Design and execute advanced statistical analyses to guide product, marketing, and operations decisions.
- Plan and analyze experiments and quasi-experiments, including A/B testing and power calculations.
- Develop predictive models, risk scores, and causal inference frameworks; validate and monitor model performance.
- Collaborate with data engineers to ensure reliable data pipelines and reproducible analyses.
- Prepare clear, actionable insights and present results to cross-functional teams and leadership.
- Mentor junior statisticians and contribute to statistical governance and best practices.
- Ensure compliance with data governance, ethics, and privacy standards in all work.
Qualification
- Master’s or PhD in Statistics, Biostatistics, Econometrics, or a closely related field; or equivalent industry experience.
- At least 4 years of applied statistics experience in tech, finance, healthcare, or related sectors.
- Strong knowledge of experimental design, hypothesis testing, regression analysis, time-series, and Bayesian methods.
- Proficiency in R and Python (statsmodels, scikit-learn); SQL experience; familiarity with Git.
- Experience with data visualization tools and building dashboards (Tableau or Power BI a plus).
- Excellent written and verbal communication; ability to explain complex analyses to non-technical audiences.
- Demonstrated ability to work collaboratively in cross-functional teams and manage multiple priorities.