Job description
Join Apex Analytics Group, a premier data science consultancy specializing in applied statistics across finance, healthcare, and consumer analytics. We are seeking a results-oriented Applied Statistics Analyst to design and implement robust statistical models that translate complex data into actionable business insights. This role blends rigorous methodology with cross-functional collaboration to drive strategic decisions and measurable impact. You will work with cross-functional teams to frame business problems, develop analytical plans, and communicate findings to stakeholders at all levels. We value curiosity, precision, and the ability to translate data into strategy.
Responsibility
- Develop and validate statistical models (regression, time-series, survival, Bayesian) to address business questions.
- Design and analyze experiments, including A/B tests and quasi-experimental studies, to establish causal impact.
- Clean, explore, and preprocess large datasets; implement data quality controls and robust data pipelines.
- Collaborate with product, data engineering, and leadership to translate findings into data-driven strategies.
- Communicate results through clear dashboards, reports, and presentations tailored to technical and non-technical audiences.
- Ensure reproducibility through well-documented code, version control, and peer reviews; contribute to best practices.
- Mentor junior analysts and contribute to training and methodological knowledge sharing.
- Monitor model performance in production; iterate and refine models as data and business needs evolve.
Qualification
- Master's degree in Statistics, Biostatistics, Mathematics, or a closely related field; PhD preferred.
- 3+ years of hands-on applied statistics experience in industry or equivalent setting.
- Proficiency in R and Python (pandas, numpy, scikit-learn); strong SQL skills.
- Experience with experimental design and causal inference methods (A/B testing, propensity score, difference-in-differences).
- Strong data visualization and storytelling; ability to communicate complex results to non-technical stakeholders.
- Familiarity with data pipelines, data wrangling, and working with cloud platforms (AWS or GCP) is a plus.
- Solid software development practices: version control (Git), reproducible research, and documentation.
- Ability to work independently and collaboratively in a fast-paced, cross-functional environment.