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Statistics 🏢 Full Time ⭐️ Verified

Senior Statistician

ApexQuant Analytics
San Francisco, CA
Salary Estimate
USD 120.000 – USD 180.000
Posting Time
5 Mei 2026
Deadline
5 Mei 2027

Job description

Join ApexQuant Analytics as a Senior Statistician and elevate our data driven culture. You will design and implement robust statistical models, lead experimental design, and translate insights into strategic recommendations for stakeholders across product, marketing, and operations.

We seek a collaborative, detail oriented statistician who thrives in a fast paced environment and brings a strong foundation in applied statistics, data visualization, and reproducible research.

Responsibility

  • Design, implement, and validate statistical models to inform product, marketing, and operational decisions.
  • Lead experimental design and A/B testing, including power analysis and sample size planning.
  • Develop forecasting and time series models to support planning and scoping.
  • Collaborate with data engineers to ensure data quality, reproducibility, and scalable pipelines.
  • Communicate complex results to non-technical stakeholders with clear visuals and storytelling.
  • Mentor junior analysts and contribute to code reviews and best practices.
  • Build and maintain dashboards and recurring performance reports.

Qualification

  • MS or PhD in Statistics, Mathematics, Economics, Data Science, or related field.
  • 5+ years of applied statistics experience in industry or research settings.
  • Proficiency in R and Python (pandas, numpy, scipy); SQL.
  • Strong knowledge of experimental design, hypothesis testing, regression modeling, and Bayesian methods.
  • Experience with time series forecasting and basic machine learning concepts.
  • Excellent communication and collaboration skills with stakeholders at all levels.
  • Experience with data visualization tools and reproducible research practices.

Required Skills

statistical modelling R Python SQL experimental design hypothesis testing time series data visualization machine learning basics data wrangling reproducible research Bayesian methods

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