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Data Science 🏢 Full Time ⭐️ Verified

Lead Applied Statistics Analyst

QuantBridge Analytics
Cambridge, MA
Salary Estimate
USD 120.000 – USD 170.000
Posting Time
7 Mei 2026
Deadline
7 Mei 2027

Job description

QuantBridge Analytics, a premier data science consultancy, is seeking a Lead Applied Statistics Analyst to join our Cambridge, MA team. This role blends rigorous statistical theory with practical, business-focused analytics to help clients make evidence-based decisions.

In this role, you will collaborate with cross-functional teams, mentor junior analysts, and translate complex analyses into clear, actionable insights. The ideal candidate thrives in a fast-paced environment and has a track record of delivering measurable impact through statistical thinking.

Why QuantBridge Analytics?

  • Competitive salary and comprehensive benefits
  • Hybrid work flexibility
  • Opportunities to lead high-impact projects
  • Strong focus on professional development and mentorship

Responsibility

  • Design and oversee statistically rigorous analyses to answer business questions, including experimental design, sample size calculations, and hypothesis testing.
  • Lead model development and validation using techniques such as regression, time-series, generalized linear models, and Bayesian methods.
  • Collaborate with product, engineering, and commercial teams to translate insights into actionable recommendations.
  • Develop reproducible analysis pipelines in R and Python; document methods for auditability.
  • Mentor and coach junior statisticians and data scientists; promote growth and best practices.
  • Communicate results through clear data visualization and storytelling for non-technical audiences.
  • Stay current with statistical methodologies and industry best practices to drive impact across clients.

Qualification

  • Master's or PhD in Statistics, Mathematics, Econometrics, or a related field.
  • 5+ years of applied statistics experience in industry or consulting.
  • Strong proficiency in R; Python and SAS are a plus.
  • Extensive experience with experimental design, regression, time-series, and Bayesian methods.
  • Proficient in SQL and data visualization tools (ggplot2, seaborn, Tableau, or Power BI).
  • Excellent communication and stakeholder management skills; ability to convey complex results clearly.
  • Proven track record of delivering actionable insights that drive business outcomes.
  • Ability to manage multiple priorities in a fast-paced environment.

Required Skills

Applied statistics R Python SAS SQL experimental design Bayesian statistics regression analysis time-series machine learning data visualization statistical consulting STATA

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