Data Scientist

This Data Scientist is instrumental in the development of insights, models, and advanced analyses to drive measurable, profitable data-driven decision-making across Safelite's business. This position combines disparate data from multiple internal and external sources, determines the best model to address the business question at hand, creates actionable insights, and contributes to a holistic understanding of consumer behavior as it relates to Safelite products and services.

What You’ll Do

• Identify and apply optimal statistical analysis, supervised, and unsupervised modeling techniques to drive decision-making and KPI improvement; techniques may include A/B and multivariate testing, predictive analysis, clustering, anomaly detection, and exploratory analyses.
• Discover, quantify, and make actionable data-driven conversion opportunities across a variety of data domains, including customer experience, supply chain, and field operations.
• Manage the modeling and insights portion of the data science pipeline independently, from data tidying, preparation, and visualization to model creation and training; support and learn from senior team members to expand into the data acquisition and model deployment portions of the data science lifecycle.
• Support the testing of key conversion and pricing strategies, including the ability to model and present key financial results and outcomes.
• Performs other duties as assigned.
• Comply with all policies and standards.

What You’ll Need

• Bachelor’s degree in Statistics, Analytics, or related quantitative field.
• Minimum 1-3 years relevant experience as a data scientist or advanced analyst.
• Strong problem-solving skills, detail-oriented, and ability to manage multiple projects simultaneously.
• Experience with modeling for practical business execution: Demonstrated expertise in developing, validating, and implementing models that have driven concrete business value.
• Strong in Microsoft Excel and Tableau or similar BI tools, with direct experience presenting model-driven insights and trends to stakeholders.
• Demonstrated competence in tidying, visualization, descriptive and predictive statistical analysis, machine learning, and model delivery using at least one modern open-source statistical programming language.
• Intermediate understanding of applied statistics and fundamental machine learning concepts.
• Familiarity with and understanding of e-commerce, digital and voice lead channels, and B2C pricing strategies.
• Intermediate SQL skills: Demonstrated experience querying databases and integrating data from multiple sources.
• Intermediate experience with top statistical programming languages (i.e., R or Python).