Decision Scientist

Farmers Insurance Careers

2d•Hybrid

About The Position

This position provides critical decision support across the enterprise, with a focus on insurance lead marketplace and distribution initiatives, by gathering, analyzing, and synthesizing data to address business challenges. The role applies moderately advanced mathematical, statistical, and quantitative techniques to draw conclusions and deliver actionable recommendations that drive efficiency, growth, and profitability. It interprets larger datasets to extract meaningful insights and trends and then communicates insights and recommendations to business partners and leadership to support informed decision-making. The role may informally mentor or train less experienced team members to support their work quality. The position performs work independently while receiving limited guidance and coaching.

Requirements

Minimum three years of work experience required in data analysis, statistical or mathematical modeling, or related.
High School Diploma or equivalent required.
Strong verbal communication and listening skills.
Proven storytelling skills with ability to communicate complex data insights and recommend clearly to technical and non-technical audiences.
Demonstrated written communication skills.
Demonstrated analytical skills.
Demonstrated problem solving skills.
Effective interpersonal skills.
Ability to influence internal and/or external constituents.
Seeks to acquire knowledge in area of specialty.
Demonstrated time management and priority setting skills.
Possesses strong technical aptitude.
Proficient in Microsoft Office suite.
Proficiency in applying moderately advanced statistical and machine learning concepts and tools.
Working knowledge of data analysis and manipulation tools (SQL, Python, SAS, R, and/or Snowflake).
Working knowledge of data visualization tools (example, Tableau, Power BI).
Proficiency in working with datasets including data wrangling and data munging.
Able to adapt quickly to new technologies.

Nice To Haves

Experience in insurance industry preferred.
Experience in marketplace, lead generation, marketing analytics, or distribution analytics a plus, but not required.
Bachelors degree preferred in data science, statistics, mathematics, business analytics or similar.
Equivalent work experience may be considered in lieu of degree.
Experience with MediaAlpha or other lead aggregation data.
Experience with Quinstreet or other sales and marketing automation.

Responsibilities

Applies moderately advanced mathematical, statistical, and quantitative techniques to solve medium-to-large scale business problems, particularly related to lead marketplace performance (e.g., growth, conversion, mix, efficiency), that significantly impact current and future business strategies. Builds descriptive or explanatory models or uses the output of models created by others.
Analyzes large datasets, including internal and external (vendor) marketplace data to identify trends, patterns, and business opportunities. Leverages interactive data visualization tools and statistical techniques such as distribution analysis, correlation analysis, outlier detection, multivariate analysis, time series, machine learning, and others to uncover hidden insights. Conducts thorough exploratory data analysis (EDA) to uncover opportunities including testing hypotheses and validating findings with business partners.
Facilitates discussions with cross- functional business partners to understand marketplace-related business objectives and teams to understand and collaborate on complex business objectives. Influences solution strategies and outcomes by leveraging expanded knowledge of the business. Uses proficient experience in data analysis to provide insights that support decision-making, balancing growth, profitability, and operational considerations.
Collects data from a variety of sources and integrates and transforms disparate datasets to create cohesive datasets for analysis. Assesses data quality and applies data hygiene techniques to ensure accuracy and consistency. Supports data reliability by conducting quality checks, documenting data processes, and collaborating with more experienced analysts for peer review and data validation as needed.
Coordinates with cross-functional technical teams including IT, data scientists, data engineers and others to ensure data integrity and optimize data pipelines in support of analytical and reporting needs (e.g., performance tracking, impact measurement). Identifies data quality issues and collaborates to resolve them. Assists deployment and monitoring of more complex predictive models into workflows.
Builds and maintains repeatable analyses and translates technical data insights into communications and presentations for non-technical business partners and leadership to ensure data-driven insights and recommended action plans are easily understandable. Uses intermediate storytelling approaches to make complex information more accessible and actionable, including communicating implications, risks, and trade-offs
Stays informed about emerging decision and data science methodologies, tools, and best practices. Applies knowledge and continuous learning to improve the quality of own work and the work of others on the team. May informally mentor or train less experienced team members to support their work quality. Actively seeks feedback from more experienced team members and engages in professional development opportunities to enhance skills and contribute effectively to team objectives. Performs other duties as assigned.