LEAD DATA SCIENCE - PRICING
Job Overview
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.
Responsibilities
• 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 productionize, 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 business cases and guide proposals through qualification and prioritization.
• Define and execute analytical product roadmaps by evaluating business value, model feasibility, data readiness, and technical dependencies while balancing near-term priorities with long-term strategy.
• Lead requirements gathering and cross-functional alignment with Sales, Product Management, Finance, Customer Care, Engineering, IT, and business-unit stakeholder’s
• Lead requirements gathering and cross-functional alignment with Sales, Product Management, Finance, Customer Care, Engineering, IT, and business-unit stakeholder’s
What your background should look like:
• 5+ years of experience in AI/advanced analytics, pricing analytics, commercial analytics a comparable role supporting complex business decisions.
• Experience with pricing, commercial, customer, product, and related decision processes is preferred,
• Graduate degree (MS or MBA) in Computer Science, Analytics, Statistics, Information Systems, Economics, Finance, Business, or a related quantitative field preferred.
• Equivalent combination of relevant education and experience may be considered book-price effectiveness, margin improvement, agreement performance, transactional.
• Margin achievement, price realization, and quote conversion versus business targets
• Book-price, agreement, pricing, and tariff-recovery performance versus plan
• Reduction of transactional and tariff-related margin leakage
• Accuracy, transparency, timeliness, and adoption of pricing analytics and reporting
• Automation and AI enhancement of pricing workflows, recommendations, monitoring, and exception handling
• Execution of pricing strategies, prioritized roadmaps, playbooks, and continuous-improvement initiatives
• Effective stakeholder alignment, communication, and measurable business value