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Progressive Insurance · 1 day ago

Data Scientist Lead

Ohio, United States

Full-time

Hybrid

Senior Level, Lead/Staff

$115K/yr - $165K/yr

6+ years exp

Progressive Insurance is dedicated to helping employees move forward in their careers. As a lead data scientist on the CRM Acquisition Experience organization, you'll work on AI/ML projects that drive personalization in the Quote flow, designing and deploying traditional AI models to enhance customer experiences.

Auto InsuranceAutomotiveCommercial InsuranceHealth InsuranceInformation TechnologyInsuranceLogistics

Growth Opportunities

No H1B

U.S. Citizen Only

Responsibilities

Design, build, and deploy traditional AI models that create high-quality experiences for prospective customers through coverage recommendations, additional offers, and more

Be a driving force in emerging Generative and Agentic AI strategic efforts, including virtual assistants, search experiences, and other related initiatives

Qualification

Statistical ModelingMachine LearningPythonSQLAWS Machine LearningLarge Language ModelsLinuxCommunication SkillsCollaboration Skills

Required

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

Proven track record of successfully creating, deploying, and evaluating statistical and machine learning models in a high-volume and/or real-time environment

Strong proficiency in Python and SQL (Snowflake, SQL Server) to collect and manipulate data

Familiarity with Large Language Models (LLMs), such as OpenAI ChatGPT, to enhance products, and a proficiency in the Linux operating system, shell scripting, and command line usage

Experience with AWS Machine Learning and support services (S3, EC2, Lambda, SageMaker, Cloudwatch) and MLOps frameworks (GitHub Actions, Jenkins)

Excellent communication and collaboration skills, with the ability to convey complex technical concepts to non-technical collaborators