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.

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. 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 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…