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Analytics 🏢 Full Time ⭐️ Verified

Senior Applied Statistician

NovaQuant Analytics
Boston, MA
Salary Estimate
USD 120.000 – USD 180.000
Posting Time
7 Mei 2026
Deadline
7 Mei 2027

Job description

NovaQuant Analytics is seeking a Senior Applied Statistician to drive advanced statistical analyses in pharmaceutical, healthcare, and technology projects. You will collaborate with cross-functional teams, design experiments, build predictive models, and translate results into actionable recommendations for stakeholders. The ideal candidate combines deep statistical knowledge with practical, impact-driven delivery.

This role offers a collaborative, fast-paced environment where rigor and communication are valued. Hybrid work options available in the Boston area.

Responsibility

  • Lead the design and execution of statistical analyses for complex business and research projects across multiple domains.
  • Develop and validate predictive, causal, and Bayesian models to inform decision making.
  • Collaborate with data engineers, data scientists, and product teams to define analysis plans and data requirements.
  • Prepare clear, audience-friendly reports and data visualizations for executives and non-technical stakeholders.
  • Ensure rigorous methodology, reproducibility, and thorough documentation of all analyses.
  • Mentor junior analysts and contribute to the development of statistical standards and best practices.
  • Translate study results into actionable business recommendations and measurable metrics.

Qualification

  • Master's degree or PhD in Statistics, Biostatistics, Mathematics, or a related field.
  • 5+ years of applied statistics experience in industry (pharma, life sciences, healthcare, or tech).
  • Proficiency in R; strong Python and SQL skills; experience with SAS is a plus.
  • Solid knowledge of experimental design, regression analysis, survival analysis, Bayesian methods, and basic machine learning.
  • Experience with data visualization tools (Tableau, Power BI) and communicating technical results to non-technical audiences.
  • Strong problem-solving, project management, and collaborative skills; ability to translate data into actionable insights.
  • Familiarity with regulatory considerations (e.g., GCP) is a plus.

Required Skills

Statistical Modeling R Python SQL SAS Bayesian Methods Experimental Design Hypothesis Testing Data Visualization Tableau Power BI Data Wrangling Machine Learning Basics Experimentation Reproducible Research Statistical Software Development

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