About the role
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As a lead data scientist on the Claims Control - File Owner team, you'll analyze and develop algorithms for technology solutions that solve business problems and improve operational efficiency. You’ll leverage structured and unstructured customer data to build, test, and evaluate statistical and machine learning models. You’ll partner with business and technical collaborators to translate customer insights into actionable recommendations and support the deployment and monitoring of data-driven solutions within customer-facing processes.
Work products may range from ad hoc analyses and recommendations for internal partners to direct integration into production systems used by tens of thousands of users.
This is a remote position for U.S.- based work only, requiring occasional travel for meetings and/or training.
Minimum qualifications
A minimum of 6 years of relevant experience in Statistical/Quantitative Modeling and/or Machine Learning tools and in using various database tools processing large volumes of structured and unstructured data.
{OR} Bachelor's degree with quantitative focus in Econometrics, Statistics, Operations Research, Computer Science or related field (e.g. Mathematics) and a minimum of 3 years of relevant experience in Statistical/Quantitative Modeling and/or Machine Learning tools (R, Python, etc.) and in using various database tools (e.g. Hadoop, SQL) processing large volumes of structured and unstructured data.
{OR} Master's degree or higher with quantitative focus in Econometrics, Statistics, Operations Research, Computer Science or related field (e.g. Mathematics) and a minimum of 1 year of relevant experience in Statistical/Quantitative Modeling and/or Machine Learning tools (R, Python, etc) and in using various database tools (e.g. Hadoop, SQL) processing large volumes of structured and unstructured data.
Preferred skills
Demonstrated experience building, deploying, and monitoring statistical and machine learning models in Python, including model validation, evaluation, and performance tracking.
Hands-on experience analyzing structured and unstructured data to develop customer insights, predictive models, and actionable business recommendations.
Experience designing and maintaining production data pipelines and predictive data flows that support analytics and machine learning solutions.
Experience using cloud-based analytics and machine learning platforms like AWS, and partnering with senior business collaborators and cross-functional teams to deliver solutions.
Experience leading or mentoring junior data scientists and familiarity with emerging analytics technologies such as generative AI, large language models (LLMs), and graph databases, with Neo4j experience.
Compensation
$115,400-$164,800/year
Gainshare annual cash incentive payment up to 40% of your eligible earnings based on company performance.
Benefits
401(k) with dollar for dollar company match up to 6%.
Medical, dental, and vision, including free preventive care.
Wellness and mental health programs.
Health care flexible spending accounts, health savings accounts, and life insurance.
Paid time off, including volunteer time off.
Paid and unpaid sick leave, as well as short and long term disability.
Parental and family leave; military leave and pay.Diverse, inclusive, and welcoming culture with Employee Resource Groups.
Career development and tuition assistance.
Onsite gym and healthcare at large locations.
Energage recognizes Progressive as a 2026 Top Workplace for: Innovation, Purposes & Values, Work Life Flexibility, Compensation & Benefits, and Leadership.
Equal Opportunity Employer
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Sponsorship for work authorization is available for this position only for candidates who hold an existing H-1B Visa.
Minimum requirements
- 6+ years experience in statistical/quantitative modeling or machine learning with large structured/unstructured data
- OR Bachelor's in quantitative field plus 3+ years relevant experience with tools like R, Python, Hadoop, SQL
- OR Master's or higher in quantitative field plus 1+ year relevant experience with statistical/machine learning tools and databases
This listing was parsed by AI and may not be complete. Check the official posting on Progressive's site for the most accurate information.