Live opening · Posted 4 days ago

Data Scientist Senior

Progressive Insurance · United States (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 4 days ago
CompanyProgressive Insurance
LocationUnited States (Remote)
Salary401(k), +1 benefit
Work modeYes
SkillsPython, AWS
SourceLinkedin
ListedPosted 4 days ago

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About the role

Description supplied by the original job listing.

Progressive is dedicated to helping employees move forward and live fully in their careers. Your journey has already begun. Apply today and take the first step to Destination: Progress.
As a senior data scientist on the Personal Lines Research & Development Underwriting & Verification (UV+) team, you'll develop and deploy advanced analytics and machine learning solutions that improve rating accuracy, strengthen underwriting risk management, and enhance the customer experience. Using large, complex datasets, you'll build scalable predictive models and analytical solutions that support driver verification and underwriting strategies across the policy lifecycle. Working across data science, data engineering, cloud technologies, and model monitoring, you'll partner with business and technical partners to translate complex problems into actionable insights and deliver measurable operational and financial impact for Progressive.
This is a remote position for U.S.- based work only, requiring occasional travel for meetings and/or training.
Must-have Qualifications
A minimum of 5 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, bachelor's degree with quantitative focus in Econometrics, Statistics, Operations Research, Computer Science or related field (e.g. Mathematics) and a minimum of 2 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).
Preferred Skills
Demonstrated experience developing, validating, and deploying machine learning models using Python, SQL, and modern data science libraries.
Strong knowledge of supervised learning, feature engineering, model evaluation, interpretability, and predictive modeling for structured data.
Experience building data pipelines and working with large datasets from multiple internal and external sources.
Familiarity with cloud platforms, preferably Amazon Web Services, and technologies such as Snowflake or MLOps tools.
Strong communication and collaboration skills, including the ability to translate business needs into analytical solutions and explain technical findings to varied audiences.
Compensation
$89,600-$119,500/year
Gainshare annual cash incentive program up to 30% of your eligible earnings, based on company performance.
Benefits
401(k) with dollar-for-dollar company match up to 6%.
Medical, dental & vision, including free preventative care.
Wellness & mental health programs.
Health care flexible spending accounts, health savings accounts, & life insurance.
Paid time off including volunteer time off.
Paid & unpaid sick leave where applicable, as well as short & long-term disability.
Parental & family leave; military leave & pay.
Diverse, inclusive & welcoming culture with Employee Resource Groups.
Career development & tuition assistance.
Energage recognizes Progressive as a 2025 Top Workplace for: Innovation, Purposes & Values, Work-Life Flexibility, Compensation & Benefits, and Leadership.
Equal Opportunity Employer
Sponsorship for work authorization is available for this position only for candidates who hold an existing H-1B Visa.
For ideas about how you might be able to protect yourself from job scams, visit our scam-awareness page at https://www.progressive.com/careers/how-we-hire/faq/job-scams/

Work arrangement
Yes

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