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Lead Data Scientist

6657

We are Farmers!

Join a team of diverse professionals at Farmers to acquire skills on the job and apply your learned knowledge to future roles at Farmers. Farmers Insurance also offers extensive training opportunities through the award winning University of Farmers named by Training magazine amongst top 10 corporate training units in the world.

Job Summary

  • Full-stack Lead Data Science with an interest in applying advanced analytics and modeling to improve business results.
  • Leverage customer information such as macro and micro/transactional behavioral data to influence strategic business decisions while using complex, innovative analytics, multi-variate models, machine learning and data mining technologies.
  • Leader of a group of data scientists applying state of the art analytics, modeling, and ETL to Distribution, Life and Financial Services challenges.
  • Leads operationalizing business decisions.
  • Drive home a Measures of Success culture within Farmers with a focus on profitable growth initiatives. 
  • Deepen and expands the data science toolkits available to Farmers. 
  • Considers business, strategy, and IT implications in all initiatives. 
  • Manage a team of data scientists.  Passionate about team engagement, development, and well-being.
  • Great opportunity to join a growing team, make a difference to the bottom line at Farmers, have fun, and enjoy a culture with good work life balance.

Essential Job Functions

  • Own and drive home complex and often vague business challenges involving data science. Succeeds in projects by (1) scoping, (2) defining measures of success, (3) having a data science vision for project success, and (4) executing successfully.  Executes on projects with a sense of urgency succeeding in hitting deliverable dates.
  • Partners closely with IT, business, and data management/engineering teams to understand, utilize, and improve our data infrastructure.  Advises and serves as an objective and transparent partner to drive fact-based decision making and a measures of success culture.
  • Responsible for a solid knowledge of consumer analytics including closure models, retention models, agency economics, and lead optimization.
  • Hands on ability with advanced programing, complex ETL and specialized modeling methods to drive home projects and lead the team through examples of good technical skills. Python, GitHub, Machine Learning and multi-variate modeling SQL, ETL software like snowflake.
  • Manages model deployments via MLOps techniques.  Works with analytics and IT teams to deploy models/rules in platforms like Algorithmia.  Will help steer MLOps environment improvements.
  • Ability to present complex information clearly.  Good presentation skills from entry level to seniorr managers [up to medium sized groups].  Makes complex technical material simple to non-technical people.  Can run meetings efficiently.
  • Manages a team of data science professionals.  Ability to bring the best out of the team. Good coaching acumen around technical and non-technical skills.

Education Requirements

  • Bachelors and Master’s Degree in Statistics, Economics, Data Science, Mathematics or related field preferred.  On the job experience could substitute for Master’s degree. 

Experience Requirements

  • 5-10+ years of relevant experience such as data science, analytics, economics, operations research, and/or statistics experience.  Insurance background preferred but not required.
  • Track record of success solving quantitative problems using data science for complex business questions with a focus on consumer behavior.

Job Location(s): US - AZ - Remote, US - TX - Austin-LngVista, US - CA - Remote, US - MI - Remote, US - TX - Remote, US - FL - Remote, US - NY - Remote, US - OH - Remote, US - PA - Remote, US - WA - Remote, US - GA - Remote, US - IL - Remote, US - MA - Remote, US - NC - Remote

Want to learn more about our culture & opportunities? Check out farmers.com/careers and be sure to follow us on Instagram and LinkedIn!


Nearest Major Market: Phoenix

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