Job description
Join Nova Analytics Labs as an Applied Statistics Scientist, where you will design and implement robust statistical models that drive decision making across healthcare, finance, and technology clients. You will collaborate with cross-functional teams to translate data into actionable insights, communicate results clearly, and contribute to a culture of rigorous analytics.
We value curiosity, clarity, and communication. You will work with data engineers, analysts, and business partners to ensure robust analyses, reproducible code, and meaningful impact.
Responsibility
- Lead development and validation of predictive models using R, Python, or SAS.
- Design and execute experiments and quasi-experimental studies to establish causal relationships.
- Collaborate with data engineers to source, clean, and wrangle complex datasets.
- Translate statistical results into actionable business insights for stakeholders across functions.
- Ensure model governance, documentation, and reproducibility across projects.
- Mentor junior analysts and present findings through clear visualizations and compelling stories.
Qualification
- Master's degree in Statistics, Biostatistics, Mathematics, or related field; PhD preferred.
- 3+ years of applied statistical analysis in industry or research settings.
- Proficiency in R and Python; experience with SAS is a plus.
- Strong knowledge of regression, time series, experimental design, and hypothesis testing.
- Experience with SQL and data visualization tools (Tableau, Power BI, or similar).
- Excellent communication skills and ability to explain complex methods to non-technical audiences.
- Strong problem-solving skills and attention to detail.