Farmers seeks to improve business results by applying advanced analytics and modeling, leveraging customer information and behavioral data to influence strategic business decisions using complex, innovative analytics, multi-variate models, machine learning, and data mining technologies.
Requirements
- Demonstrated proficiency working on large-scale structured and unstructured multidimensional data using moderately advanced knowledge of open-source cloud-enabled analytical programming languages.
- Developing ability to consult on data extraction, data manipulation and data design for statistical, modeling and monitoring needs.
- Moderately advanced knowledge of data analysis, manipulation tools (SQL, Python, SAS, R, and/or Snowflake) and cloud computing services (AWS).
- Working knowledge of data visualization tools (example, Tableau, Power BI).
- Developing 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.
- Moderately advanced proficiency in predictive and prescriptive modeling using advanced machine learning and deep learning techniques.
- Working knowledge of ML/AI model deployment best practices.
Responsibilities
- Utilizes knowledge of consumer analytics including retention models, agency economics, and lead optimization in their daily work.
- Utilizes moderate knowledge of advanced programing, complex ETL and specialized modeling methods to execute projects.
- Demonstrates clean reusable code and effective documentation, encourages other to do the same.
- Executes on moderate level business challenges involving data science.
- Succeeds in projects by scoping, defining measures of success, utilizing a data science vision for project success, and accomplishes successfully within prescribed timelines.
- Partners closely with IT, business, and data management/engineering teams to understand, utilize, and improve our data infrastructure.
- Manages moderate model deployments via MLOps techniques.
Other
- Minimum three years of work experience required in data analysis, statistical or mathematical modeling, or related.
- 3+ years P&C insurance modeling experience.
- 3+ years professional python coding experience.
- Linux experience.
- Generalized Linear Modeling expereince.
