Statistical Scientist (M.S. or Ph.D.)

Exponent Inc.•Phoenix, AZ

53d•Onsite

About The Position

Exponent is seeking a Statistical Scientist for its Data Sciences Practice in Phoenix, AZ. This role involves participating in diverse projects that include exploratory data analysis, statistical inference, and predictive modeling. The scientist will apply risk analysis methodologies to problems across various sectors such as engineering, health, finance, ecology, and the environment. Additionally, the position will support internal and external clients in planning data collection, which includes problem framing, experimental design, sample size calculations, and identifying appropriate populations and sampling strategies. The role also requires developing reports and visualizations to address client needs and support litigation.

Requirements

Ph.D. (or M.S. degree with two years' work experience post-graduation) in Statistics, Biostatistics, or a related field
Excellent communication skills and the ability to communicate statistical concepts to non-technical audiences
Experience or capabilities in such subject areas as statistical data mining, analysis of reliability and life data, experimental design, Bayesian statistics, machine learning, or quality control/improvement
Minimum of two years' experience with one or more statistical software packages (SAS and R are preferred)
Ability to work independently and in multidisciplinary teams
Presently legally authorized to work in the United States; no immigration sponsorship or processing required

Nice To Haves

Programming skills (e.g., C++, SQL, Visual Basic, Python) and software or dashboard development experience are strongly preferred

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
Providing support to internal and external clients when planning data collection, including framing the problem, experimental design, sample size calculations, and identifying appropriate populations and sampling strategies
Developing reports and visualizations to address clients’ scientific and engineering problems and to support litigation