Lead Data Scientist - Experimentation

State Farm State Farm · Insurance · Bloomington, IL +3 · Research and Data Analytics

Lead Data Scientist focused on experimentation and A/B testing to help business partners examine new ideas and quantify the impact of strategic decisions. This role involves designing experiments, developing advanced analytic models, and educating others on experimentation across the enterprise. Requires a Master's degree and experience in predictive model building, A/B testing, and statistical programming languages like Python, R, or SAS. Experience in regulated environments is preferred.

What you'd actually do

  1. As a data scientist on the Enterprise Experimentation Team, you will help business partners examine new ideas by formulating hypotheses and designing experiments to test hypotheses, allowing them to accurately and confidently quantify the impact of their strategic decisions.
  2. You will serve as a subject matter expert, consultant, and advocate for experimentation.
  3. Through this role, you will work to educate others on experimentation and grow the knowledge base of experimentation across the company.
  4. Develop and validate advanced analytic models, designed experiments, and other data-driven solutions
  5. Provide input into and/or build datasets to support solution development

Skills

Required

  • Masters degree in an analytical field
  • 3+ years of predictive model building experience
  • Practical work experience with, and understanding of, topics associated with A/B testing and other experimental design concepts for business contexts
  • Ability to communicate basic statistical concepts (e.g., statistical significance, confidence intervals, regression models) to business partners
  • Experience building advanced analytic solutions using generalized linear models and at least one of the following: time series analysis, cluster analysis, tree-based algorithms, or neural networks
  • Experience with at least one statistical programming language: Python, R, or SAS

Nice to have

  • Experience with mixed linear & non-linear model methodologies
  • Experience with statistics-based experimental designs, causal inference, or difference-in-difference based estimation
  • Experience with cloud-based environments (e.g., AWS) or Linux
  • Strong communication skills and the ability to manage multiple, diverse stakeholders across business areas and leadership levels
  • Experience gathering and interpreting business requirements for designing scalable data science solutions in a regulatory environment (e.g., insurance, healthcare, and finance)

What the JD emphasized

  • regulatory environment