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 a diverse 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 SUMMARY

Utilizes specialized knowledge and experience to apply advanced analytics and modeling to improve business results. Leverages unique customer information and behavioral data to influence strategic business decisions while using complex, innovative analytics, multi-variate models, machine learning and data mining technologies. Assists in and leads complex, cross-functional projects operationalizing business decisions. Works independently receiving guidance in only the most complex situations. The role mentors, coaches, and trains less experienced team members and supervises direct reports who are individual contributors.

EDUCATION YOU’LL NEED

• High School Diploma or equivalent required.
• Masters degree required in data science, statistics, mathematics, business analytics or related.

ADDITIONAL QUALIFICATIONS

• Strong verbal communication and listening skills. Advanced storytelling skills with ability to communicate complex data insights clearly to technical and non-technical audiences.
• Demonstrated written communication skills.
• Proficient in Microsoft Office Suite.
• Develops and delivers effective presentations.
• Effectively coaches and delivers constructive feedback.
• Demonstrated problem solving skills.
• Excellent collaboration and team building skills.
• Ability to influence internal and/or external constituents.
• Seeks to acquire knowledge in area of specialty.
• Possesses flexibility to work in a fast paced, dynamic environment. Able to meet deadlines and priorities that shift with business needs. Able to simultaneously handle multiple priorities. Possesses solid project management skills.
• Demonstrated analytical skills. Possesses advanced technical aptitude.
• Advanced proficiency working on large-scale structured and unstructured multidimensional data using advanced knowledge of open-source cloud-enabled analytical programming languages. Advanced ability to consult on data extraction, data manipulation and data design for statistical, modeling and monitoring needs. Advanced knowledge of data analysis, manipulation tools (SQL, Python, SAS, R, and/or Snowflake) and cloud computing services (AWS). Advanced knowledge of data visualization tools (example, Tableau, Power BI).
• Advanced proficiency in using explanatory, diagnostic, and inferential techniques such as experimental design, hypothesis testing, clustering analysis, time series and other statistical modeling algorithms with the ability to decide the appropriate methodology for the purpose. Advanced proficiency in predictive and prescriptive modeling using advanced machine learning and deep learning techniques. Advanced in ML/AI model deployment best practices. Able to adapt quickly to new technologies. Advanced knowledge of coding standards and version control (Git). Other. Broad knowledge of data ethics and data privacy.

• Takes ownership and executes on more complex and often vague business challenges involving data science. Succeeds in specialized projects by scoping, defining measures of success, utilizing a data science vision for project success, and exceeding on prescribed and some vague timelines. Executes and leads broad projects independently with a sense of urgency. Utilizes specialized knowledge of consumer analytics including retention models, agency economics, and leads optimization in their daily work.
• Utilizes broad knowledge of advanced programing, complex ETL and specialized modeling methods to execute projects and leads the team through examples of effective technical skills. Demonstrates clean reusable code and effective documentation, encourages others to do the same. Acts as the main contributor to multiple phases of a data science project (ideation, experiment design, EDA, feature engineering, model building, deployment, etc. ). Utilizes a strong sense of ownership and contributes to multiple tasks and deadlines simultaneously.
• Partners closely with IT, business, and data management/engineering teams to understand, utilize, and improve our data infrastructure. Advises on complex matters and serves as an objective and transparent partner to drive fact-based decision making and a measures of success culture. Provides strategic direction, project clarity and methodological consultation. Delivers results both individually and by mentoring and empowering other team members.
• Mentors and provides guidance to team members. Provides high level coaching and knowledge around technical and non-technical skills. Reviews AI/ML modeling, statistical analysis, and data analysis completed by other team members, providing coaching and feedback as needed.
• Develops presentations and presents to all groups and levels of leadership, including executives. Regularly communicates complex technical material understandable to non-technical associates.
• Manages specialized model deployments via MLOps techniques. Partners closely with analytics and IT teams to deploy models/rules in various platforms and leads testing of new solutions. Takes active role in steering MLOps environment improvements.