Data Scientist

Farmers Insurance•Los Angeles, CA

19d•$137,469•Hybrid

About The Position

We are Farmers – where ambition meets opportunity. At Farmers, we’re not just known for unforgettable jingle – we’re a team with a passion for purpose and making a real difference in people’s lives. We deliver peace of mind when it matters most. Our results-driven, high-performance culture thrives on creativity, accountability and bold solutions. Here, growth isn’t just a goal – it’s a way of life for both the organization and every individual on our team. We tackle challenges head-on, learn from every experience and measure our impact on the customers who trust us. Join an award-winning, equal opportunity employer, where you’ll find more than a job – you’ll find a supportive community. Enjoy competitive benefits, take part in meaningful volunteer projects, and help shape the future alongside talented colleagues across all backgrounds. At Farmers, helping others is at the heart of what we do. Ready to make your mark? Discover our vibrant culture and explore career opportunities at www.Farmers.com/careers/corporate. Connect with us on Instagram, LinkedIn and TikTok, and let’s build something incredible together! 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.

Requirements

Master’s degree, or foreign equivalent, in Statistics, Business Analytics, or a closely related field of study, plus 3 years of experience in the job offered, or as a Predictive Analyst, Senior Predictive Analyst, or similar position applying analytics and modeling techniques.
3 years of experience with communicating complex data insights to technical and non-technical audiences.
3 years of experience with influencing internal and external stakeholders.
3 years of experience with applying data ethics and data privacy principles.
3 years of experience with working in a fast-paced, high-volume environment while meeting production deadlines.
3 years of experience with processing large-scale structured and unstructured multidimensional data using open-source, cloud-enabled analytical programming languages.
3 years of experience with consulting on data extraction, manipulation, and design for statistical modeling and monitoring needs.
3 years of experience with performing data analysis using SAS, SQL, and Python.
3 years of experience with working with the Snowflake data platform, including maintaining Snowflake workspaces for modeling data.
3 years of experience with performing data engineering tasks including extraction from relational databases, transformation, cleaning, validation, and analysis.
3 years of experience with creating data visualizations using Tableau and Power BI.
3 years of experience with applying explanatory, diagnostic, and inferential techniques including experimental design, hypothesis testing, clustering analysis, and Generalized Linear Modeling.
3 years of experience with selecting appropriate methodologies and techniques for analytical objectives.
3 years of experience with building predictive and prescriptive models using advanced machine learning and deep learning techniques.
3 years of experience with implementing ML/AI model deployment best practices.
2 years of experience with applying coding standards and version control using Git.
2 years of experience with working on cross-functional teams, including product implementation and testing.

Responsibilities

Execute on moderate business challenges involving data science.
Succeed in projects by scoping, defining measures of success, utilizing a data science vision for project success and accomplish successfully within prescribed timelines.
Execute at the intermediate level projects with a sense of urgency (25%).
Utilize conceptual knowledge of consumer analytics including retention models, agency economics, and lead optimization in their daily work.
Utilize moderate knowledge of advance programming, ETL and specialized modeling methods to execute projects.
Demonstrate clean reusable code and effective documentation, and encourage others to do the same (30%).
Partner closely with IT, business, and data management/engineering teams to understand, utilize, and improve data infrastructure.
Advise on fundamental concerns and serve as an objective and transparent partner to drive fact-based decision making and a measure of success culture (15%).
Develop presentations and present to leadership, occasionally communicate complex technical material understandable to non-technical associates (10%).
Manage moderate model deployments via MLOps techniques.
Work with analytics and IT teams to deploy models/rules in various platforms and support testing of new solutions (10%).
Mentor junior data science team members and provide coaching and knowledge around technical and non-technical skills (10%).