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Statistics & Data Science 🏢 Full Time ⭐️ Verified

Senior Applied Statistician

NovaMetrics Analytics
Boston, MA
Salary Estimate
USD 110.000 – USD 155.000
Posting Time
2 Mei 2026
Deadline
2 Mei 2027

Job description

Join our fast growing analytics team as a Senior Applied Statistician in Boston, MA. You will design and execute statistical analyses to drive product decisions, marketing optimization, and operational insights. Collaborate with data engineers, data scientists, and business leaders to translate data into actionable insights.

Responsibility

  • Lead experimental design for A/B tests and other experiments, ensuring valid causal inferences.
  • Develop and validate statistical models to forecast outcomes and optimize strategies.
  • Collaborate with product and marketing teams to translate analytics into actionable recommendations.
  • Assess data quality, identify data gaps, and implement robust data quality checks.
  • Document methods, assumptions, and results; present findings to nontechnical stakeholders.
  • Mentor junior analysts on statistical methods and best practices.
  • Ensure reproducibility by building reusable code and standard operating procedures.

Qualification

  • Master or Doctoral degree in statistics, biostatistics, mathematics, or a related field.
  • 5+ years of applied statistics experience in industry or consultancy.
  • Proficiency in R and Python for data analysis and modeling; experience with SAS is a plus.
  • Strong knowledge of linear and generalized linear models, mixed effects models, and time series analysis.
  • Experience with experimental design, hypothesis testing, and causal inference methods.
  • Strong data wrangling skills (SQL, data pipelines) and ability to work with large datasets.
  • Excellent communication skills and ability to present complex results to nontechnical audiences.
  • Demonstrated collaboration skills and project management ability.

Required Skills

statistical modeling experimental design hypothesis testing R Python SAS SQL data visualization data wrangling machine learning basics

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