Decision Scientist

Farmers Insurance Careers

2d•$96,075 - $182,625•Hybrid

About The Position

This position provides critical decision support across the enterprise 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 then communicates findings 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 in our Business Insurance Line of Business.

Requirements

Minimum three years of work experience required in data analysis, statistical or mathematical modeling, or related.
Strong verbal communication and listening skills.
Proven storytelling skills with ability to communicate complex data insights 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, Property and Casualty and Business Insurance a plus.

Responsibilities

Applies moderately advanced mathematical, statistical, and quantitative techniques to solve medium-to-large scale business problems that significantly impact current and future business strategies. Builds descriptive or explanatory models or uses the output of models created by others.
Analyzes larger datasets 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 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.
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. Identifies data quality issues and collaborates to resolve them. Assists deployment and monitoring of more complex predictive models into workflows.
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.
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.