Statistical Scientist (Ph.D.)

Exponent•Phoenix, AZ

1d•Onsite

About The Position

Exponent is the only premium engineering and scientific consulting firm with the depth and breadth of expertise to solve our clients’ most profoundly unique, unprecedented, and urgent challenges. We are committed to engaging multidisciplinary teams of science, engineering, and regulatory experts to empower our clients with solutions that create a safer, healthier, more sustainable world. For over five decades, we've connected the lessons of past failures with tomorrow's solutions to advise clients as they innovate technologically complex products and processes, ensure the safety and health of their users, and address the challenges of sustainability. Join our team of experts with degrees from top programs at over 500 universities and extensive experience spanning a variety of industries. At Exponent, you’ll contribute to the diverse pool of ideas, talents, backgrounds, and experiences that drives our collaborative teamwork and breakthrough insights. Plus, we help you grow your career through mentoring, sponsorship, and a culture of learning. Thanks for your interest in joining our team! We are currently seeking a Statistical Scientist for our Data Sciences Practice to be based in our Phoenix, AZ office. In this role, you will work as part of a team to help our clients solve challenging technical problems which are often urgent, high profile, and multi-disciplinary. You will also support non-clinical work in the pharmaceutical and biotech industries, so experience with assay development, immunogenicity assessment, and manufacturing are a plus. You will be involved in a variety of projects in application areas including manufacturing, construction, automotive, health, and consumer products. You will have the opportunity to define and shape your individual consulting practice based on your skills and interests. At Exponent, we have found that in-person interactions deepen employee engagement and are crucial for development, for realizing the full potential of our talented and diverse teams, and for building a more inclusive workplace where all have a sense of belonging. In our offices, you can expect a supportive culture and a collaborative, dynamic, multi-disciplinary work environment. Our consultants engage in-person in the office unless they are traveling for client work or other business activities. We value the rich lives our colleagues enjoy outside of work and understand that work/life balance is critical to our employees and their well-being. Consultants have the autonomy to balance their work and personal schedules so you can meet with clients, visit inspection sites, attend conferences, and make time for priorities outside of work, too. It is this flexible, agile work style and working hours that allow our teams to drive innovation and results in their own ways, while meeting the needs of clients.

Requirements

Ph.D. in Statistics or Quality Engineering
Significant research in theoretical or applied statistical methods
Excellent communication skills and the ability to communicate statistical concepts to non-technical audiences
Experience or capabilities in such subject areas as statistical data analysis, analysis of reliability and life data, sample plan development, experimental design, and/or quality control/improvement
Minimum of two years' experience with one or more statistical software packages (SAS, R, Python, and JMP or Minitab are a plus)
Ability to work independently and in multidisciplinary teams
Required proof of U.S. citizenship and the possession of, or ability to obtain, a U.S. public trust security clearance or higher, for our contracts with the United States Government

Nice To Haves

Experience with assay development, immunogenicity assessment, and manufacturing are a plus
Programming skills (e.g., JSL, SQL, Visual Basic, R, Python), 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, manufacturing, health, finance, 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
Measuring and providing guidance on the quality and reliability of products, systems, and organizations
Assisting pharmaceutical and biotech customers with product optimization, assay development, stability analyses, and manufacturing improvements
Developing reports and visualizations to address clients’ scientific and engineering problems and to support litigation