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Statistics / Data Science 🏢 Full Time ⭐️ Verified

Senior Applied Statistician

ApexStat Analytics
Cambridge, MA
Salary Estimate
USD 120.000 – USD 180.000
Posting Time
5 Mei 2026
Deadline
5 Mei 2027

Job description

Join ApexStat Analytics, a leading data science consultancy, as a Senior Applied Statistician in Cambridge, MA. You will apply rigorous statistical methods to solve complex business problems for enterprise clients, deliver actionable insights, and help shape the analytics strategy of the firm.

We value methodological rigor, clear communication, and collaborative problem solving. This role offers opportunities for mentorship, leadership, and professional growth in a fast-paced, data-driven environment.

Responsibility

  • Lead the design, execution, and interpretation of applied statistical analyses across client engagements.
  • Develop and validate predictive models, forecasting tools, and experimental designs (A/B and multivariate experiments).
  • Collaborate with product, engineering, and business teams to translate business questions into statistical solutions.
  • Apply Bayesian and frequentist methods to real-world data; build robust inference pipelines with documentation.
  • Communicate complex statistical results to non-technical stakeholders using clear visuals and concise narratives.
  • Ensure reproducible research through code review, version control, and well-documented workflows.
  • Mentor junior statisticians and contribute to modeling standards and best practices.

Qualification

  • PhD or MS in Statistics, Biostatistics, Mathematics, or a closely related field; 4+ years of applied statistics experience in industry preferred.
  • Strong expertise in statistical modeling (regression, survival analysis, time-to-event, multivariate methods) and experimental design.
  • Proficiency in R and Python; experience with SAS, SQL, and data visualization tools is a plus.
  • Experience with Bayesian methods and modern machine learning approaches in applied settings.
  • Excellent communication skills with ability to explain complex results to non-technical audiences.
  • Experience with reproducible research practices: version control (Git), notebooks, and documentation.
  • Domain experience in healthcare analytics, finance, or consumer analytics is advantageous.

Required Skills

Statistics Statistical Modeling R Python Bayesian Methods Regression Survival Analysis Experimental Design Data Visualization SQL Git

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