Data Scientist Lead

McLane is one of the largest and most stable supply chain services leaders in the United States. We’ve been at the forefront of delivering retail and restaurant solutions for convenience stores, mass merchants, drug stores, and chain restaurants for over 125 years. Our vision is to be an agile, innovative, and unified supply chain partner that delivers a superior customer experience, improves the lives of our teammates and community, and produces best-in-class returns.

McLane Company seeking an experienced and highly analytical Senior Data Scientist with deep domain knowledge in Finance and Customer Profitability Modeling to join our growing data science team. In this role, you will lead the development of analytical models and tools that evaluate customer value, improve financial decision-making, and optimize pricing, contracts, and service strategies across the business. You will work cross-functionally with Finance, Sales, Commercial, and Technology teams to translate complex data into actionable insights that directly impact the bottom line.

This is a hybrid position which will require the candidate to report and work from the office three days a week. Therefore, interested candidates should be within a 50-minute radius from Temple, TX.

Benefits you can count on:

Day 1 Benefits: medical, dental, and vision insurance, FSA/HSA, and company-paid life insurance

Paid holidays, earn vacation time, and sick leave accrual from day one.

401(k) Profit Sharing Plan after 90 days.

Additional benefits: pet insurance, maternity/paternity leave, employee assistance programs, discount programs, tuition reimbursement program, and more!

Essential Job Functions:

Lead design and implementation of customer profitability models to assess margin contribution, lifetime

value, and account-level economics.

Develop and maintain predictive models using statistical and machine learning techniques (e.g., regression,

clustering, decision trees, ensemble methods).

Partner with Finance and Sales to create a customer segmentation framework based on financial contribution, cost-to-serve, risk, and growth potential.

Analyze product, pricing, operational, and financial data to uncover drivers of profitability and identify

margin improvement opportunities.

Collaborate with BI and data engineering teams to ensure robust data pipelines and model deployment

infrastructure.

Build interactive dashboards and visualizations to support business users in scenario analysis and decision-making.

Support pricing, promotion, and contract optimization initiatives through data-driven recommendations.

Communicate findings and recommendations clearly to senior executives and non-technical stakeholders.

Minimum Skills & Qualifications:

Bachelor’s or Master’s degree in Data Science, Statistics, Applied Mathematics, Finance, Economics, or

related field (PhD preferred).

7+ years of experience in data science or advanced analytics, preferably in finance or consulting

environments.

Proven experience building models for customer profitability, pricing strategy, or financial forecasting.

Strong command of SQL and at least one programming language (Python, R, or Scala).

Expertise in machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow) and statistical modeling.

Experience working with large-scale structured and unstructured data sets.

Proficiency in data visualization tools (e.g., Power BI, Tableau, or similar).

Strong business acumen and ability to translate complex analytics into financial impact

Preferred Qualifications:

Prior experience in B2B or supply chain, logistics, or distribution industries.

Exposure to activity-based costing (ABC) and financial margin analysis.

Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and model deployment best practices.

Experience with contract analytics or incentive modeling is a plus.

Working Conditions:

Office environment.

Hybrid.

Candidates may be subject to a background check and drug screen, in accordance with applicable laws.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Schedule: Full-time

Shift: 1st - Day