Director, Value Quantification, Product Data & Analytics

Job Title:

Director, Value Quantification, Product Data & Analytics

Overview:

Overview
Product Data & Analytics is a centralized global team that enables Mastercard product business units to make better data‑driven decisions. We build internal analytics partnerships that strengthen focus on business performance, portfolio and revenue optimization, initiative tracking, new product development, and go‑to‑market strategies. These capabilities are underpinned by our data platforms that enable insights to be delivered in a standardized, scalable, and cost‑efficient manner.
As Director, Value Quantification, you will own the data, models, and analytics that power Mastercard’s value quantification platform. You will be responsible for designing, building, and operationalizing scalable data assets, value models, and analytics tools that quantify the economic impact of Mastercard’s products and services. This role partners closely with product, pricing, sales, and customer success teams to ensure value drivers are rigorously measured, consistently modeled, and embedded into enterprise platforms, enabling credible, data‑driven value storytelling that drives customer adoption, revenue growth, and retention.
Key Responsibilities
• Define and lead the value quantification strategy across the product lifecycle, embedding consistent ROI and value measurement into product, pricing, sales, and customer success
• Own and scale value models and analytics assets, including ROI frameworks and simulation tools, ensuring robustness, transparency, and adaptability
• Drive productization of the value quantification platform, partnering with engineering to deliver scalable, automated, enterprise-grade solutions
• Enable value-based pricing and commercial decisions through close partnership with pricing, finance, and product teams
• Drive cross-functional adoption, working with services, product, sales, and customer success to embed value quantification into workflows and strengthen value storytelling
• Establish a single, governed source of truth for value analytics, ensuring consistency of data, models, and KPIs across the organisation
• Lead AI-enabled innovation in value modelling, improving predictive capabilities and automating insight generation
• Define governance and standards for model accuracy, auditability, and enterprise consistency
• Build and lead a high-performing team, fostering a culture of innovation, accountability, and measurable impact
• Deliver measurable business outcomes, driving revenue growth, pricing optimisation, and improved customer value articulation
Qualifications
Experience
• Experience designing, developing, and scaling data‑driven tools, frameworks, and analytics products with clear, measurable business outcomes, including value quantification, pricing, or customer impact use cases.
• Demonstrated success partnering with cross-functional teams, including Sales, Marketing, Product, and Customer Service Center leads, translating business strategy and requirements into scalable technical solutions, and communicating outcomes and trade‑offs effectively.
• Strong leadership skills with a passion for mentoring and developing a high-performing team, and the ability to foster a culture of collaboration, innovation, and continuous learning while ensuring alignment with business goals.
• Background in analytics, data science, pricing strategy, customer success, or related fields; experience in financial services or payments is strongly preferred.
Skills
• Strong technical expertise in modern data platforms and big‑data ecosystems, including Ozone/Cloudera Hadoop, AWS, Databricks, OneLake, and SQL‑based analytics across hybrid and cloud‑adjacent architectures.
• Strong analytical and problem‑solving skills, with the ability to derive actionable insights from complex, multi‑source datasets and operate effectively in ambiguous problem spaces.
• Solid technical acumen with the ability to design, review, and guide the implementation of advanced analytics, data models, and visualization solutions using Python, SQL, and BI tools.
• Deep understanding of value‑based pricing, customer success enablement, and revenue optimization concepts, and how analytics supports commercial decision‑making.
• Excellent communication and storytelling skills, with the ability to translate complex technical insights into clear, business‑relevant narratives for both technical and non‑technical audiences.
• Strong collaboration skills and a team‑oriented mindset, with the ability to work effectively across product, engineering, sales, pricing, and customer success teams.
Education
• Bachelor’s degree in Data Science, Computer Science, Business Analytics, Economics, Finance, or a related field.
• Advanced degrees (MBA, Master’s, or certifications in analytics, data science) are preferred

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