Farmers Insurance is one of the United States’ largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, Farmers Insurance is part of one the largest Insurance Groups in the world.
About the Role
We are looking for a Predictive Analytics Manager to join a newly established, high-impact team focused on transforming enterprise decision-making. This team is at the forefront of delivering timely, accurate, and forward-looking financial and operational insights by combining advanced analytics, actuarial concepts, automation, and AI-enabled capabilities.
In this role, you will help build predictive analytics capabilities from the ground up in a fast-paced, “startup-like” environment within a large organization. You will play a key role in designing and implementing data-driven solutions that drive profitable growth, improve operational efficiency, and strengthen business intelligence across the enterprise.
This is an excellent opportunity for a data-driven professional who enjoys autonomy, thrives in ambiguous environments, and wants to influence how analytics is built and scaled.
What You’ll Do-
Develop and implement predictive models using advanced statistical and machine learning techniques (e.g., regression, clustering, decision trees, neural networks)
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Build and maintain programs for predictor and response variables, ensuring model accuracy and scalability
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Partner with business stakeholders to understand needs, translate them into analytical solutions, and communicate actionable insights clearly
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Present analytical findings to non-technical audiences, explaining methodologies, data sources, and business impact
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Explore, prepare, and structure large datasets (internal and external) to support model development and enhancement
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Contribute to the design and continuous improvement of modeling frameworks, processes, and best practices
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Ensure data quality and model integrity through rigorous validation and review processes
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Develop a strong understanding of the data landscape, including sourcing, mapping, and integrating data across systems
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Support enterprise data initiatives (e.g., data migration and transformation programs)
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Collaborate with and mentor junior analysts, sharing knowledge and promoting best practices
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Stay current on industry trends, particularly within insurance analytics and predictive modeling
Requirements
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6+ years of experience in predictive analytics, data science, or related field
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Bachelor’s degree in Mathematics, Statistics, Computer Science, or related field
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Professional experience in insurance or pricing analytics is a strong plus
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Strong experience with:
- Python, R, and SQL
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Experience with SAS is a plus
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Advanced knowledge of:
- Predictive modeling and machine learning techniques
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Statistical analysis and data mining
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Data preparation and feature engineering
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Strong understanding of data ecosystems and ability to navigate complex data environments
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Ability to translate complex data into clear, actionable insights
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Excellent communication skills, with the ability to present analytical findings to diverse audiences
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Problem-solving mindset with the ability to work independently in a fast-evolving environment
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Experience contributing to or building analytics capabilities from scratch is highly valued
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Collaborative and proactive approach, with a willingness to share knowledge and mentor others
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Experience working with cross-functional teams in data-driven environments
Benefits
Competitive compensation and benefits package:
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Comprehensive benefits package
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Career development and training opportunities
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Flexible work arrangements
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Dynamic and inclusive work culture within a globally renowned group
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Private Health Insurance
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Pension Plan
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Paid Time Off
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Training & Development
Note: Benefits differ based on employee level.
