Sr. Data Scientist

Farmers Insurance Careers

6h•$108,375 - $205,750•Hybrid

About The Position

We are Farmers! We are… more than just your favorite commercials.  At Farmers, we strive to deliver peace of mind to our customers by providing protection and comprehensive advice and delivering in the moments of truth. That means having people who can help us meet changing customer and business needs. Farmers high-performance culture is focused on results and the people who achieve them. We hold ourselves and others accountable for sustainably growing the business and each other. We seek solutions, own our actions, and grow through discomfort. We see setbacks as opportunities while continuously asking ourselves how we impact our customers. Farmers is an award winning, equal opportunity employer, committed to the strength of an inclusive workforce. We are dedicated to supporting the well-being of our people through our extensive suite of benefits, as well as the well-being of the communities we serve through employee volunteer programs and nonprofit partnerships. Helping others in their time of need isn’t just our business – it’s our culture!  To learn more about our high-performance culture and open opportunities, check out www.Farmers.com/careers/corporate and be sure to follow us on Instagram, LinkedIn, and TikTok. Workplace: Hybrid ( #LI-Hybrid ), Remote ( #LI-Remote ) Farmers believes in a culture of collaboration, creativity, and innovation, which thrives when we have the ability to work flexibly in a virtual setting as well as the opportunity to be together in person. Our hybrid work environment combines the best of both worlds with at least three (3) days in office and up to two (2) days virtual for employees who live within fifty (50) miles of a Farmers corporate office. Applicants beyond fifty (50) miles may still be considered.Job SummarySeeking an experienced Senior Data Scientist to lead advanced data modeling initiatives that support automation and drive digital transformation across the business. In this important individual contributor role, you will provide exploratory and predictive modeling services for various lines of business and shared functions, working independently and as part of a team. You’ll collaborate closely with business leaders to identify opportunities, clarify requirements, and deliver end-to-end AI/ML solutions that streamline workflows, accelerate decision-making, and improve risk quality. You will extract and clean complex datasets, build and rigorously test models, and present results clearly to demonstrate business value. Through your work, you will help automate our quoting process, enhance customer experience, and increase efficiency throughout the organization.

Requirements

5-7 years as Data Scientist or related technical role in a delivery oriented environment required.
Experience within the insurance industry and insurance data preferred.
5-7 years of experience building and deploying machine learning models in production environments with proven track record of building models that impact business KPIs
Advanced proficiency in Python and ML frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch).
Expert proficiency in data management programming (SQL) and real-time data processing pipelines.
Experience integrating and working with third-party data APIs and ETL pipelines.
Strong written and oral communication skills; ability to present to senior executives and non-technical stakeholders.
Well-organized and able to lead projects from a technical standpoint.

Nice To Haves

Experience leading projects using CRISP-DM or similar frameworks.
Experience with insurance data and industry-specific modeling.
Knowledge of AI-powered development tools (e.g., GitHub Copilot) for accelerated model development.
Proven expertise in processing automation and workflow optimization using ML/AI.
Mastery of advanced statistical and machine learning concepts, including regression, GLMs, decision trees, ensemble modeling, clustering, and SVM.

Responsibilities

Lead the design, build, and validation of quantitative models (descriptive, predictive, optimization/simulation) for underwriting automation and other business functions.
Develop and deploy ML solutions that accelerate quote-to-bind processes, automate risk assessment, and enable straight-through processing for standard risks.
Create sophisticated risk and customer segmentation strategies; build real-time scoring engines to support instant decisioning.
Pull, clean, and manage datasets; design models using advanced statistical and machine learning concepts (e.g., regression, GLMs, decision trees, ensemble modeling etc.,).
Own business outcomes (OKRs and KPIs) and communicate results and insights to business leaders and stakeholders.
Perform research and development on new algorithms, modeling concepts, and technical tools; recommend adoption of new approaches into our analytics toolkit.