Job description
Join Nova Analytics, a leading data science firm, as a Senior Statistician in Cambridge, MA. You will lead the design and implementation of robust statistical models that inform product strategy, clinical insights, and customer analytics.
As part of a cross-functional team, you will translate business questions into rigorous analyses, ensure reproducibility, and communicate complex results to non-technical stakeholders.
We offer a collaborative environment, competitive compensation, and opportunities to work on high-impact problems across industries.
Responsibility
- Design and implement robust statistical models to inform product strategy and operational decisions.
- Translate business questions into analysis plans; define metrics, hypotheses, and evaluation criteria.
- Clean, preprocess, and validate large datasets; ensure data quality and reproducibility.
- Develop, test, and maintain code for analyses (R/Python), documenting workflows for reproducibility.
- Apply advanced methods (Bayesian inference, time-series, causal inference, experimental design) to real-world problems.
- Collaborate with data engineers, data scientists, and product stakeholders; present findings through dashboards and reports.
- Mentor junior analysts; contribute to best practices, governance, and knowledge sharing.
- Communicate complex results to non-technical audiences; produce executive summaries.
Qualification
- Master’s or PhD in Statistics, Mathematics, Data Science, or related field.
- 3+ years of applied statistics or data science experience; strong quantitative background.
- Proficiency in R and Python (pandas, numpy, scipy, scikit-learn); SQL experience.
- Experience with experimental design, A/B testing, and causal inference.
- Data wrangling and visualization skills (ggplot2, seaborn, Tableau/Power BI).
- Strong communication and stakeholder management; ability to explain results clearly.
- Familiarity with cloud platforms (AWS/GCP/Azure) and reproducible workflows (Git, Docker).
- Ability to work independently in a fast-paced environment and manage multiple priorities.