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Data Science 🏢 Full Time ⭐️ Verified

Senior Applied Statistician

NovaStat Analytics
Cambridge
Salary Estimate
USD 120.000 – USD 160.000
Posting Time
8 Mei 2026
Deadline
8 Mei 2027

Job description

NovaStat Analytics is seeking a Senior Applied Statistician to join our growing analytics team in Cambridge, MA. This role blends rigorous statistical methodology with real world data to shape strategic decisions across life sciences, healthcare, and consumer analytics.

In this role, you will partner with data scientists, engineers, clinicians, and product leaders to design robust studies, implement state of the art statistical models, and translate quantitative insights into actionable business recommendations.

What we offer: competitive salary, flexible work options, professional development, and a collaborative culture that values curiosity and impact.

Responsibility

  • Lead the design of experiments including randomized trials and observational studies, with rigorous power analyses and sample size planning.
  • Develop and implement statistical models (linear and generalized linear models, mixed effects, survival analysis, and Bayesian methods) to answer complex client questions.
  • Clean, analyze, and interpret large datasets; ensure reproducibility through well-documented code and workflows.
  • Collaborate with data scientists, engineers, clinicians, and product teams to translate results into actionable recommendations.
  • Communicate results to non technical stakeholders via dashboards, reports, and presentations; create clear visualizations.
  • Mentor junior statisticians and analysts; contribute to internal methodology and best practices.
  • Ensure compliance with data privacy, ethical standards, and regulatory requirements; contribute to statistical analysis plans and study protocols.

Qualification

  • PhD in Statistics, Biostatistics, Data Science, or related field; or MS with 5+ years of applied statistics experience.
  • Strong programming skills in R and Python; experience with SAS is a plus.
  • Expertise in experimental design, regression, survival analysis, mixed effects models, and Bayesian methods.
  • Proven ability to analyze complex datasets, draw actionable insights, and communicate results effectively.
  • Experience with SQL and data wrangling; familiarity with big data tools is a plus.
  • Strong collaboration, project management, and written/verbal communication skills.
  • Track record of delivering impact in life sciences, healthcare, or consumer analytics; publications or presentations are a plus.

Required Skills

R Python SQL SAS Bayesian methods linear and generalized linear models mixed effects survival analysis experimental design data wrangling data visualization reproducible research cross-functional collaboration

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