Job description
Nova Analytics Labs is seeking a Senior Applied Statistician to join our analytics team in Cambridge, MA. You will apply rigorous statistical methods to real-world business problems, design experiments, and translate complex analyses into clear, strategic recommendations.
In this role, you will collaborate with data engineers, product managers, and researchers to define analysis plans, implement robust models, and communicate results to non-technical stakeholders. You will own end-to-end analyses from data exploration to report delivery and help mentor junior analysts.
We offer a collaborative, growth-focused environment, competitive compensation, and the opportunity to influence key decisions across multiple business units.
Responsibility
- Lead and execute applied statistical analyses on diverse datasets to inform product, marketing, and operations decisions.
- Design and analyze experiments, including A/B tests and quasi-experimental studies; perform power calculations and sample size determinations.
- Develop predictive and prescriptive models using R and Python; validate models and ensure reproducibility through version control and documentation.
- Collaborate with data engineers to ensure data quality, reproducibility, and robust data pipelines; define data requirements and lineage.
- Develop dashboards and reports that translate complex results into actionable business insights for cross-functional teams.
- Present findings to non-technical stakeholders with clear storytelling and data visualization; prepare documentation for governance and audit trails.
- Mentor junior analysts, share best practices in statistics and analytics, and contribute to internal training and methodology development.
Qualification
- Master's or PhD in Statistics, Biostatistics, Mathematics, or a related field, or equivalent professional experience.
- Minimum 3 years of applied statistics experience in industry or research settings.
- Strong proficiency in R; Python is required or preferred; experience with SAS/SPSS is a plus.
- Solid knowledge of experimental design, causal inference, multivariate analysis, and machine learning basics.
- Experience with SQL and data wrangling; familiarity with cloud data platforms (BigQuery, Snowflake) is a plus.
- Excellent communication and collaboration skills; ability to present complex analyses to non-technical audiences.
- Attention to detail, strong problem-solving, and ability to manage multiple projects with competing deadlines.