Data Scientist: Predictive Analytics for Customers & Agents

Farmers Insurance; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation

Performance-based bonuses

Comprehensive benefits

Training and development resources

Job summary

Farmers Insurance is seeking a Data Scientist to develop predictive models, analytics solutions and actionable insights that improve customer retention and agent performance. You’ll partner with stakeholders to identify opportunities and translate objectives into measurable outcomes.

The ideal candidate blends machine learning, statistics, Python and SQL with the ability to communicate complex results to non-technical audiences and influence business decisions.

Qualifications

• Bachelor’s or master’s in a quantitative field.
• 3+ years in data science or analytics.
• Strong Python and SQL skills with production experience.
• English fluency and ability to explain insights.

Responsibilities

• Develop and deploy predictive and prescriptive analytics models.
• Apply ML, statistics and data mining to business problems.
• Analyze large datasets for trends and actionable insights.
• Design and maintain scalable, production analytics solutions.
• Collaborate with stakeholders to translate objectives into metrics.
• Work with Data Engineering, IT, and Analytics teams on deployment.
• Follow ML Ops practices and document code and models.
• Present findings to technical and non-technical audiences.
• Support customer retention, servicing and operational performance.
• Mentor junior team members and share best practices.

Skills

Python

SQL

GitHub

Microsoft Office

Databricks

Machine Learning

Statistics

English fluency

Education

Bachelor's degree in Data Science / Stats / CS

Tools

Databricks

Job description

Farmers Insurance is seeking a Data Scientist to develop predictive models, analytics solutions and actionable insights that improve customer retention and agent performance. You’ll partner with stakeholders to identify opportunities and translate objectives into measurable outcomes.

The ideal candidate blends machine learning, statistics, Python and SQL with the ability to communicate complex results to non-technical audiences and influence business decisions.