Lead Data Scientist

Does this position interest you? You should apply – even if you don’t match every single requirement! We're known as an auto glass company. That's the focus of what we do. But beyond the glass, we're so much more. We'll help you build a fulfilling career and encourage you to have a life. Let us be the best place you'll ever work.


A Brief Overview
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. This position 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 and 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 problem

• 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

• Performs other duties as assigned

• Complies with all policies and standards

What You Will Need

• 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 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 (In Office): It is expected that you will primarily perform work at the Safelite Home Office (7400 Safelite Way, Columbus, OH 43235). You are required to work in the office at least 4 days a week. Changes to work location arrangements are subject to managerial approval and business needs. #LI-Onsite #LI-JR2 

This job description in no way states or implies that these are the only duties to be performed by an employee occupying this position. Employees may be required to perform other related duties as assigned to ensure workload coverage. This job description does NOT constitute an employment agreement between the employer and employee and is subject to change by the employer as the organizational needs and requirements of the job change.

This position description is not all inclusive for every aspect of this role. Reasonable accommodations will be made for individuals covered by ADA, ADEA, FMLA and other laws and regulations in accordance with their requirements. Physical and mental demands are not, and should not be construed to be job qualification standards, but are illustrated to help the employer, employee and/or applicant identify tasks where reasonable accommodations may need to be made when an otherwise qualified person is unable to perform the job’s essential duties because of an ADA disability.

Other qualifications may be required to ensure employment eligibility in accordance with local laws, regulations and with Safelite Group, Inc. policies and practices.