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# Staff Data Scientist - Databricks

- **Company:** The Information Technology
- **Location:** Bloomington, IL, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Python (Programming Language), Machine Learning, SQL Databases, Information Technology, Databricks
- **Published:** October 23, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=21cee1f4a341bd5a

## About the Role

* 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.

## Description

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.