Lead Data Science - Pricing

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.

The Lead Data Science-Pricing role is an AI and advanced analytics position with specialized responsibility for pricing and commercial decision support. The role frames complex business challenges as data, AI and analytical opportunities; develops insights and analytical products; and applies these capabilities to quote pricing, book-price effectiveness, margin improvement, agreement performance, transactional pricing leakage, tariff recovery, customer segmentation, market intelligence, and pricing opportunities.

The role partners across Sales, Product Management, Finance, Customer Care, Engineering, IT, and business teams to define pricing strategies and solution roadmaps, automate pricing workflows, guide execution, communicate recommendations, track adoption and measurable value.

• Gather integrate and validate pricing, customer, product, cost, agreement, transaction, market and quote data from enterprise, ERP, cloud, and external sources.
• Perform exploratory analysis and automate recurring data collection, pricing uploads or downloads, price-request support, and reporting workflows.
• Develop dashboards and visualizations in relevant pricing platforms to provide transparent and actionable insights. r
• Define and execute pricing strategies, governance, KPIs, customer and product playbooks, tariff-recovery actions, and commercial initiatives aligned with business objectives and market dynamics.
• Drive process and system optimization, balancing price improvement and transactional execution while improving book-price effectiveness, agreement performance, low-margin business, pricing leakage, and realized versus expected recovery.
• Design scalable pricing logic, business rules, and decision frameworks that use AI and automation to assess incoming opportunities, recommend competitive prices, improve quote conversion, and support appropriate human review.
• Segment industries, customers, and products; apply marketplace, competitor, economic, supply-chain, volume, and customer-sensitivity insights to pricing decisions.
• Analyze quote and opportunity demand signals, winning prices, customer behavior, product mix, competitive price movements, and distributor or external market data to identify pricing opportunities.
• Balance short-term margin improvement with long-term customer and commercial strategy; track adoption, value generation, conversion, pricing outcomes, and tariff-recovery performance.
• Design advanced analytics and AI algorithms, conversational AI, and Generative AI solutions for pricing and commercial use cases such as book price effectiveness, low margin business, tariff recovery & price leakage.
• Use experimentation, model-performance measures, and continuous monitoring to compare approaches, validate hypotheses, identify risks and opportunities, and refine recommendations.
• Partner with engineering, and IT teams to product ionize, integrate, scale, and monitor analytical models and AI-enabled pricing solution commercial decision support. The role frames complex business challenges as data, AI and analytical opportunities; develops insights and analytical pro
• Simplify complex analyses and pricing processes through clear presentations, dashboards, written communication, and data-driven storytelling; influence without authority and support fact-based customer negotiation guidance.
• Engage pricing leadership to translate complex pricing and commercial challenges into analytical opportunities with tangible impact on strategic priorities.
• Develop data-driven use cases through rapid prototyping and iterative analysis; prepare…