E
Not Specified Permanent

Phoenix, Arizona · USA job

Managing Scientist, Statistics (M.S. or Ph.D.)

Exponent

Phoenix, Arizona

Job description

Overview

In this role, you will apply statistical methods to diverse client projects in Phoenix, leading data analysis, risk assessment, and predictive modeling. You will guide multidisciplinary teams to solve urgent, high-profile problems across health, engineering, and finance. You will develop client relationships and contribute to business growth while mentoring scientists. The role sits in Exponent's Data Sciences Practice, contributing to a mission of making safer, healthier, sustainable solutions.

Compensation / Benefits
  • mentoring and sponsorship
  • culture of learning
  • health and well-being programs
  • competitive benefits
  • flexible work style
  • diverse and inclusive environment
Responsibilities
  • Participating in diverse projects involving exploratory data analysis, statistical inference, and predictive modeling
  • Applying risk analysis methodologies to problems in engineering, health, finance, ecology, and the environment
  • Management of complex projects involving multiple tasks and multidisciplinary teams
  • Development of relationships and generation of business with new and existing clients
  • Mentoring and supervision of talented Scientists and Senior Scientists in statistics
Key requirements
  • Ph.D. or M.S. degree with a minimum of seven years of work experience in Statistics or Biostatistics
  • Excellent communication skills and the ability to communicate statistical concepts to non-technical audiences
  • Experience or capabilities in subject areas such as statistical data mining, analysis of reliability and life data, experimental design, Bayesian statistics, machine learning, or quality control/improvement
  • Business development skills and professional consulting experience
  • A strong record of professional contributions as evidenced by publications or related activities
  • Excellent communication
  • Business development mindset
  • Mentoring and leadership
  • Statistical data mining
  • Reliability and life data analysis
  • Experimental design

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