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# Decision Scientist

- **Company:** Farmers Insurance
- **Location:** Phoenix, AZ, United States (Remote available)
- **Experience:** Expert
- **Salary:** $102,450.0 - $174,240.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Data Validation, Information Engineering, Data Governance, Data Visualization, R (Programming Language), Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Regression Analysis, Power BI, SAS (Software), SQL Databases, Computational Statistics, Tableau (Software), Data Analytics, Data Pipelines
- **Published:** October 3, 2026
- **Apply:** https://www.careerjet.com/job/us698d58d367f5992af728cf3cff78cd2a/eaa

## About the Role

* High School Diploma or equivalent required. Bachelor's degree preferred in data science, statistics, mathematics, business analytics or similar. Equivalent work experience may be considered in place of a degree.
 * Minimum of three years of work experience required in data analysis, statistical or mathematical modeling, or related. Experience in insurance industry preferred.
 * Demonstrated experience translating ambiguous business questions into analytical frameworks, actionable insights, and data-driven recommendations.
 * Proficiency with analytical and visualization tools such as SQL, Python, R, SAS, Tableau, Power BI, or similar technologies.
 * Experience designing, conducting, and evaluating experiments, forecasts, scenario analyses, or predictive models to influence business outcomes and strategic decision-making.
 * Strong understanding of statistical methods, hypothesis testing, regression analysis, segmentation, forecasting, and performance measurement techniques.
 * Proven ability to communicate complex analytical findings to executive and non-technical audiences, influencing decisions through clear storytelling and business acumen.
 * Insurance, financial services, risk management, or highly regulated industry experience preferred.

## Description

The Decision Scientist provides critical analytical support across the organization by gathering, analyzing, and interpreting data to solve business challenges and support strategic decision-making. This role leverages moderately advanced statistical, mathematical, and quantitative techniques to identify trends, uncover insights, and develop data-driven recommendations that improve operational efficiency, drive growth, and enhance profitability.
The ideal candidate is a strong analytical thinker who can work independently, collaborate with business partners across functions, and effectively communicate complex findings to technical and non-technical audiences. This role may also provide informal guidance and mentorship to less experienced team members.
Essential Tasks & Leadership Philosophy

 * Apply moderately advanced statistical, mathematical, and analytical techniques to solve medium-to-large-scale business problems impacting current and future business strategies.
 * Build descriptive and explanatory models or leverage outputs from predictive and machine learning models developed by others.
 * Analyze large and complex datasets to identify trends, patterns, risks, and business opportunities.
 * Utilize data visualization tools and advanced analytical methods, including: Distribution analysis, Correlation analysis, Outlier detection, Multivariate analysis, Time-series analysis, Machine learning techniques.
 * Conduct exploratory data analysis (EDA), test hypotheses, and validate findings with business stakeholders.
 * Partner with cross-functional teams to understand business objectives and develop data-driven solutions.
 * Collect, integrate, and transform data from multiple sources into cohesive datasets for analysis.
 * Evaluate data quality and apply data governance and hygiene practices to ensure reliability and accuracy.
 * Perform quality-control checks, document processes, and collaborate with peers on data validation efforts.
 * Work closely with IT, Data Engineering, Data Science, and other technical teams to optimize data pipelines and resolve data quality issues.
 * Support the deployment, monitoring, and maintenance of predictive models within business workflows.
 * Translate complex analyses into clear, actionable insights and recommendations for business leaders.
 * Utilize effective storytelling and visualization techniques to make analytical findings accessible and impactful.
 * Stay current on emerging data science methodologies, technologies, and industry best practices.
 * Contribute to a culture of continuous learning and knowledge sharing.
 * Provide informal coaching or mentorship to less experienced team members as needed.
 * Perform other duties as assigned.

First Year Success Factors
Within the first 12 months, a successful candidate can expect to have achieved the following:

 * Establish strong partnerships with business stakeholders and become a trusted analytics advisor for key initiatives.
 * Deliver actionable insights through advanced analytics, statistical modeling, and data visualization that support business decisions.
 * Lead medium-to-large analytical projects that drive measurable improvements in efficiency, growth, customer experience, or profitability.
 * Ensure data accuracy, integrity, and governance through rigorous validation, documentation, and quality control practices.
 * Identify emerging trends and opportunities, translating complex data into clear recommendations that influence leadership decisions.