Staff Data Scientist

Overview

Being good neighbors – helping people, investing in our communities, and making the world a better place – is who we are at State Farm. It is at the core of how we operate and the reason for our success. Come join a #1 team and do some good!

HYBRID: A “Hybrid” position means selected candidates will be assigned to a facility and will spend some time working both in the office and from home. For Enterprise Technology, a hybrid work arrangement will require approximately 40% in-office time each month, beginning in late 2027.
HUB LOCATIONS: Bloomington, IL; Dunwoody, GA; Richardson, TX; or Tempe, AZ 

SPONSORSHIP:  Applicants for this position are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g. H-1B visa) for this opportunity.

Responsibilities

Lead the modeling and decision science that powers personalized, coordinated engagement across acquisition, service, and retention journeys. This role is part of the Digital Growth Engine, a multidisciplinary organization focused on building a stronger learning advantage through trusted data, disciplined experimentation, intelligent decisioning, and scalable technology.

• Develop propensity, churn, lifetime value, next-best-action, recommendation, prioritization, and other decision models that support precision engagement.
• Combine behavioral, transactional, marketing, digital, and contextual signals into scalable features and decisioning approaches.
• Partner with experimentation teams to validate model-driven interventions and distinguish predictive accuracy from incremental business impact.
• Design measurement approaches for model lift, calibration, treatment effectiveness, fairness, stability, and downstream customer outcomes.
• Work with engineering and product partners to productionize models and decision services in Databricks and connected activation platforms.
• Guide identity, feature, and data requirements while accounting for privacy, consent, governance, and channel constraints.
• Mentor technical talent and establish reusable standards for precision engagement modeling and decision science.

Qualifications

• Bachelor's degree in data science, statistics, computer science, economics, engineering, mathematics, or a related quantitative field; advanced degree preferred.
• 8 plus years experience applying statistical modeling, machine learning, experimentation, or decision science to complex business problems.
• Advanced proficiency in Python and SQL, with experience working in modern cloud data and ML environments such as Databricks or comparable platforms.
• Demonstrated ability to translate ambiguous business questions into analytical approaches, production-ready models, and measurable outcomes.
• Strong communication skills with the ability to explain technical concepts, assumptions, limitations, and recommendations to technical and executive audiences.

Preferred Experience

• Experience working in a large, regulated enterprise and navigating privacy, security, legal, risk, and governance requirements.
• Experience with digital customer journeys, insurance or financial services, growth analytics, personalization, experimentation, or marketing technology.
• Demonstrated success working in cross-functional product or pod-based operating models and moving work from insight to implementation.
• A bias toward measurable outcomes, reusable capabilities, clear documentation, and continuous learning.