Senior Data Scientist, Databricks & Personalization

State Farm

Bloomington, Dunwoody, Richardson, Tempe (IL, GA, TX, AZ)

Hybrid

USD 160,000 - 220,000

Full time

3 days ago
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Benefits offered by this job

Salary range $160k-$220k
Annual bonus
Hybrid work schedule

Job summary

State Farm seeks a seasoned data science leader to drive decision science for personalized customer engagement across acquisition, service, and retention journeys. You will build and productionize models (propensity, churn, LTV, next-best-action) and partner with engineering to scale decision services in Databricks and activation platforms.

You will mentor teams, shape measurement of model lift, and ensure governance, privacy, and compliant data usage while advancing scalable analytics within a

Qualifications

  • Strong background applying statistical modeling, ML, experimentation, or decision science to business problems.
  • Ability to translate business questions into analytical approaches and production-ready models.
  • Excellent communication to explain technical concepts to diverse audiences.

Responsibilities

  • Lead modeling and decision science for personalized engagement across journeys.
  • Develop propensity, churn, lifetime value, next-best-action models and other decisioning approaches.
  • Collaborate with engineering and product teams to productionize models and services.
  • Mentor talent and establish reusable standards for precision engagement modeling.

Skills

Python
SQL
Statistics
Machine Learning
Communication
Problem Solving

Education

Bachelor's degree in data science / statistics / computer science

Tools

Databricks

Job description

State Farm seeks a seasoned data science leader to drive decision science for personalized customer engagement across acquisition, service, and retention journeys. You will build and productionize models (propensity, churn, LTV, next-best-action) and partner with engineering to scale decision services in Databricks and activation platforms.

You will mentor teams, shape measurement of model lift, and ensure governance, privacy, and compliant data usage while advancing scalable analytics within a

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