Principal Data Scientist

Worldpac•Oak Brook, IL

19d

About The Position

We’re seeking a Principal Data Scientist to lead a high-impact analytics organization focused on real-world business problems across merchandising, supply chain, sales, service, and customer-facing operations. This role is less about infrastructure build and more about shaping our AI/ML roadmap, delivering predictive and prescriptive models, translating business needs into analytics solutions, and driving measurable value across the enterprise. The Principal Data Scientist will work cross-functionally with merchandising, marketing, operations, finance, and IT to embed insights into decisions, accelerate value capture, and act as a strategic partner to the senior leadership team.

Requirements

10+ years of experience in analytics or data science, with at least 3-5 years in a leadership role (managing data science teams).
Strong track record of translating business problems into analytics/AI solutions and delivering measurable impact (e.g., revenue uplift, cost savings, new products).
Solid hands-on experience with machine learning techniques (supervised/unsupervised learning, time-series, causal inference, NLP) and a strong understanding of when/why to use them.
Comfortable making design decisions around model architecture, feature engineering, evaluation metrics, and deployment strategy.
Excellent communication and influencing skills - able to engage senior leadership, translate technical concepts into business value, build cross-functional buy-in.
With a data-driven mindset and curiosity to explore new methods, frameworks, and tools (e.g., Python, R, TensorFlow, PyTorch, SQL).
Demonstrated ability to hire, develop, and retain high-performing analytics teams and create a collaborative, accountable culture.
Master’s or PhD in a quantitative field (Analytics, Statistics, Computer Science, Engineering, Applied Math) preferred.

Nice To Haves

Experience in retail, distribution, supply chain, automotive aftermarket, or similar operations-intensive business is a plus.

Responsibilities

Develop and define the vision, strategy, and roadmap for advanced analytics and AI/ML across the company, aligned with company goals (e.g., growth, retention, margin, customer satisfaction).
Lead and mentor a team of data scientists, applied ML engineers, and analytics specialists to deliver models, experiments, and analytics workflows that drive measurable business outcomes.
Partner with business stakeholders (merchandising, supply chain, sales, operations) to identify high-value opportunities, frame analytic questions, design solutions, and quantify value (e.g., cost reduction, revenue uplift, service throughput).
Drive the full model lifecycle: problem definition, data exploration, feature engineering, model development, evaluation, deployment (through partner channels), monitoring and iteration.
Own the metrics and insights that matter: customer behavior prediction (churn, cross-sell, lifetime value), price optimization, parts demand forecasting, supply-chain disruption prediction, service center performance analytics, etc.
Translate complex analytical findings into clear, persuasive business narratives and decision-ready dashboards/presentations for senior leadership.
Stay abreast of AI/ML advances (e.g., AI/ML, large language models, causal inference, reinforcement learning) and pilot/introduce new methods where they create differentiated advantage.
Collaborate with IT and data engineering to ensure analytics access and data quality.
Establish best practices around model governance, interpretability, fairness, and ROI tracking; ensure responsible, ethical AI usage.
Define talent needs, recruit top-tier data science professionals, build a world-class analytics culture, and retain high-performing team members.