Job description
Nova Analytics is seeking a Senior Applied Statistician to lead experimental design, statistical modeling, and data-driven decision-making across client projects and internal products. You will collaborate with data scientists, engineers, and product teams to translate complex data into actionable insights.
In this role, you will design studies, validate models, and implement scalable analytics that inform strategy, drive product improvements, and measure impact.
We value rigorous methodology, clear communication, and a collaborative mindset.
Responsibility
- Design and execute experiments and quasi-experimental studies to inform product strategy and business decisions.
- Develop and validate statistical models (regression, time-series, mixed-effects, Bayesian) to forecast outcomes and quantify uncertainty.
- Lead data quality assessments, feature engineering, and reproducible analysis pipelines.
- Collaborate with cross-functional teams to translate business questions into statistical analysis plans.
- Communicate results with non-technical stakeholders, produce dashboards and data visualizations, and present insights.
- Mentor junior statisticians and contribute to best-practice methodologies.
- Ensure rigorous documentation and reproducible research practices across projects.
Qualification
- Masters or PhD in Statistics, Biostatistics, Mathematics, or a related field; 5+ years of applied statistics experience.
- Proficiency in R and Python; SQL; experience with SAS or STATA is a plus.
- Strong knowledge of experimental design, A/B testing, regression, time-series, and Bayesian methods.
- Experience building predictive models and deploying analytics in production environments.
- Excellent communication skills with the ability to explain complex concepts to non-technical audiences.
- Experience with data visualization tools (Tableau, Power BI, Looker) or similar.
- Strong problem-solving, project management, and collaboration skills.