Offer summary

Qualifications:

1 to 3 years of experience in data science or related field., Proficiency in SQL and Python programming languages., Familiarity with version control systems like GitHub and data visualization tools such as Power BI., Basic understanding of modeling and machine learning algorithms..

Key responsibilities:

Build and operationalize predictive models and conduct statistical analyses.

Extract and prepare data from various structured and unstructured sources.

Create impactful visualizations to drive business outcomes across multiple lines of business.

Support operational tasks including data validation and managing trackers in a collaborative environment.

Job description

Our client, Farmers Insurance, is one of the most established and respected insurance providers in the United States, delivering a broad range of products including home, auto, life, and commercial insurance. Founded in 1928, the company proudly serves over 10 million households nationwide, managing more than 19 million individual policies across all 50 states. They are part of the globally recognized Zurich Insurance Group, which oversees its non-claims operations via Farmers Group Inc.

With more than 48,000 exclusive and independent agents and nearly 21,000 employees, Farmers has written over US$25 billion in gross Property & Casualty premiums. The company is a market leader in Personal Lines insurance, offering specialized solutions such as dwelling fire and seasonal property coverage, designed to meet diverse customer needs and protect what matters most.

About the position

We’re looking for a motivated and detail-oriented Data Scientist I to join our team. In this role, you’ll work on end-to-end solutions that involve building and operationalizing predictive models, conducting statistical analyses, and creating impactful visualizations that drive real business outcomes across multiple lines of business or shared service functions. You’ll extract and prepare data from various sources (structured and unstructured), apply advanced analytics techniques (such as clustering, PCA, hypothesis testing, and resampling), and help deploy your models into production. You'll also support operational tasks like data validation, managing trackers, and contributing to internal communications, all while navigating shifting priorities in a collaborative, fast-paced environment.

This is a fantastic opportunity for someone early in their data science journey who is eager to grow, solve real-world problems, and contribute to high-impact projects. You’ll be part of a globally renowned group that values innovation, learning, and diverse perspectives.

Requirements

Must have