Senior Data Scientist - Pricing & ML Strategy (Remote)

Safelite; Columbus (OH); Remote; USD 160,000 - 260,000; Full time

Job summary

Safelite is seeking a Lead Data Scientist to guide end-to-end data science initiatives across Consumer Sales & Pricing. You will develop and deploy advanced machine learning and optimization models, translate insights into business recommendations, and own the deployment lifecycle from framing to production monitoring.

You will mentor junior scientists, collaborate with engineering and product teams, and influence strategic decisions with data-driven narratives, ensuring scalable, explainable

Qualifications

• Bachelor's degree in Data Science, Statistics, CS, Mathematics, Physics, Engineering or related quantitative field is required.
• Master's degree in Data Science, Statistics, CS, Mathematics, Physics, Engineering or related field is preferred.
• 7–9 years of experience in data science, ML, or advanced analytics is required.
• Proficient in SQL and have hands-on experience with regression, classification and clustering models.
• Experience in cloud-based analytics environments and ML operations (MLOps).

Responsibilities

• Lead the development of advanced ML models, statistical methods, and optimization solutions for consumer and sales growth.
• Define and enforce best practices for model development, validation, deployment and monitoring.
• Translate complex analytical outputs into actionable business insights and strategic recommendations.
• Mentor junior data scientists and collaborate with data engineering and platform teams to productionize models.

Skills

Data science leadership

SQL

ML/Analytics

A/B testing

Collaboration with engineering

Education

Bachelor's degree in quantitative field

Master's degree preferred

Tools

R

Python

Cloud platforms

MLOps

Job description

Safelite is seeking a Lead Data Scientist to guide end-to-end data science initiatives across Consumer Sales & Pricing. You will develop and deploy advanced machine learning and optimization models, translate insights into business recommendations, and own the deployment lifecycle from framing to production monitoring.

You will mentor junior scientists, collaborate with engineering and product teams, and influence strategic decisions with data-driven narratives, ensuring scalable, explainable