[Hiring] Lead Data Scientist @Safelite

Role Description

The Lead Data Scientist serves as a technical leader responsible for developing, deploying, and scaling advanced analytical, machine learning, and optimization solutions that drive measurable, profitable outcomes across Safelite’s Consumer Sales & Pricing activities. The role owns end-to-end data science solutions—from problem framing through production deployment—while translating complex analytical outputs and AI innovation into actionable business insights.

Safelite’s Consumer Sales & Pricing Team drives profitable growth by partnering with sales, product, and business leaders, to develop pricing and promotional recommendations that balance customer value with revenue goals. Their work plays a critical role in pricing optimization, experimentation strategy, and advancing the organization’s analytics capabilities through technical leadership, mentorship, and innovation.

What You Will Do

• Lead the development of advanced machine learning models, statistical frameworks, and optimization solutions to support consumer and sales growth.
• Define and enforce best practices for model development, validation, deployment, and monitoring.
• Drive innovation through the application of cutting-edge techniques, including:
  • Deep learning
  • Natural language processing (NLP)
  • Causal inference
  • Reinforcement learning
  • Emerging AI technologies
• Serve as the technical escalation point for complex analytical and modeling challenges.
• Continuously evaluate emerging methods and ensure their practical applicability to business problems.
• Own the full lifecycle of data science solutions: problem framing, feature engineering, model development, production deployment, ongoing monitoring, and improvement.
• Translate ambiguous, high-level business questions into structured analytical approaches.
• Ensure models are scalable, performant, explainable, and maintainable in production environments.
• Partner with engineering and platform teams to operationalize models.
• Work closely with senior business, sales, and product stakeholders to identify high-value use cases.
• Translate complex model outputs into actionable insights and clear strategic recommendations.
• Quantify business impact and ensure alignment with organizational KPIs, revenue goals, and growth strategies.
• Influence decision-making through compelling, data-driven narratives, not just technical outputs.
• Mentor both junior data scientists on advanced analytical methodologies and software engineering and coding best practices.
• Contribute to building a high-performance analytics culture.
• Lead knowledge sharing through code reviews, technical standards, and design discussions.
• Collaborate with data engineering, platform, and architecture teams to define data requirements, pipelines, and scalable analytics architecture.
• Advocate for data quality, governance, and reproducibility and documentation standards.
• Evaluate and integrate new tools, frameworks, and technologies into the analytics ecosystem where they deliver clear value.
• Perform other duties as assigned.
• Comply with all policies and standards.

Qualifications

• Bachelor's Degree in Data Science, Statistics, Computer Science, Mathematics, Physics, Engineering, or a related quantitative field (Required).
• Master's Degree in Data Science, Statistics, Computer Science, Mathematics, Physics, Engineering, or a related quantitative field (Preferred).
• 7-9 years of experience in data science, machine learning, applied research, or advanced analytics (Required).
• Proficient in SQL.
• Advanced experience with top statistical programming languages (R or Python).
• Experience working in cloud-based analytics environments.
• Hands-on experience building Regression models, Classification models, Clustering models.
• Strong understanding of machine learning algorithms, statistical modeling, and optimization techniques.
• Experience with A/B, multi-arm, and pre-post testing.
• Familiarity with ML operations (MLOps), including versioning, monitoring, and CI/CD pipelines.
• Familiarity with GenAI/LLMs for price recommendation explainability; competitive intelligence from unstructured data.
• Previous work on pricing strategy, pricing optimization, or pricing engines.
• Experience designing experiments without commercial testing platforms.
• Experience collaborating with data engineering and data management teams to deploy models in production, monitor model drift, and implement re-training cadences.

Expected Work Location

It is expected that you will primarily perform work remotely. You may be asked to travel, as needed, to the Safelite Home Office (7400 Safelite Way, Columbus, OH 43235), or to other location(s) as designated by the Company. Changes to work location arrangements are subject to managerial approval and business needs.