Data Scientist (Finance)

JOB DESCRIPTION A retail client is hiring Applied Data Scientists to join their Profit to Serve (PTS) initiative—a priority program driving scenario modeling and last-mile routing optimization to improve profitability and service. PTS is a foundational enabler in our AI strategy, connecting precision costing with automated insights and routing simulations. You’ll work on-site in Plano, TX, partnering directly with transformation leaders to shape a high-impact initiative at the intersection of AI, data science, and operational excellence. If you love fast iteration, hands-on coding, and solving real-world business problems, this is your opportunity to make an impact at scale. What You’ll Do • Build and iterate models for cost impact estimation, price elasticity, and routing optimization. • Design clustering approaches for route/service segmentation and validate optimization assumptions. • Translate ambiguous business questions into testable models and ship prototypes weekly. • Collaborate closely with business partners and data science leads to deliver reusable solutions. REQUIRED SKILLS AND EXPERIENCE • Strong coding skills in Python (pandas, numpy, scikit-learn) and SQL. • Experience with regression, elasticity estimation, clustering, and experimental validation. • Comfort working with optimization outputs and constraints. • Ability to wrangle data from cloud-based sources and iterate quickly with stakeholders. NICE TO HAVE SKILLS AND EXPERIENCE • Logistics simulation experience, API-driven optimization tools, and basic MLOps hygiene. Core Focus Areas • Supply Chain Knowledge: Helpful for understanding the end-to-end process—different legs, activities, and context—since the role works closely with senior leadership. • Financial Expertise: Critical priority because decisions revolve around cost-saving strategies. Everything starts with financial modeling and sensitivity analysis.