Manager, Value Enablement & Optimization

The Manager, Value Enablement & Optimization, will lead the development of data-driven frameworks, tools, and strategies that enhance value delivery across Pricing, Pre-Sales Enablement, and Customer Success. This role combines strategic thinking with technical expertise, requiring proficiency in advanced analytics, business intelligence, and automation to support scalable solutions that align with Mastercard s growth objectives. The ideal candidate is a technically skilled, innovative, and collaborative problem solver with a passion for delivering impactful insights that drive customer and revenue success.

Key Responsibilities
Strategic Support
Design and implement value enablement frameworks to support initiatives across Pricing, Pre-Sales Enablement, and Customer Success, ensuring alignment with Mastercards growth strategies.
Collaborate with global and regional stakeholders to ensure consistency and scalability of solutions, tailoring approaches to regional nuances.
Provide data-driven recommendations to optimize pricing strategies, enhance pre-sales propositions, and ensure customer success.
Technical Leadership
Develop and deploy advanced analytics tools, such as ROI calculators and value dashboards, to quantify and communicate value to clients.
Utilize programming languages such as Python, R, and SQL for data analysis, modelling, and tool development.
Leverage business intelligence platforms to create dynamic dashboards and visualizations that drive decision-making.
Drive automation and scalability by integrating AI/ML models and advanced analytics to enhance the accuracy and efficiency of tools and insights.
Value Enablement Initiatives
Build frameworks to measure and track customer value realization across the lifecycle, enabling data-driven customer engagements.
Partner with cross-functional teams to design tailored customer solutions and business cases, integrating predictive models and real-time insights.
Develop self-service analytics tools to empower customers and internal teams with actionable insights.
Revenue Optimization
Identify and implement opportunities for revenue assurance and optimization through strategic analysis and tailored customer solutions.
Monitor and analyse performance metrics to ensure alignment with revenue goals, identifying areas for improvement.
Drive post-sale optimization efforts by developing tools that track realized ROI and provide diagnostics to maximize customer outcomes.
Collaboration & Team Enablement
Work closely with cross-functional teams, including Sales, Product, Finance, and Customer Success, to ensure seamless execution of initiatives.
Foster a collaborative and innovative environment, encouraging knowledge sharing and the adoption of technical best practices.
Support training and enablement for internal teams on analytics tools and methodologies to improve efficiency and impact.

Qualifications
Experience
5+ years of experience in analytics, data science, pricing strategy, customer success, or related roles, ideally in the payments, financial services, or technology sectors.
Proven track record of developing and scaling data-driven tools and frameworks with measurable outcomes.
Expertise in programming (Python, R, SQL) and experience building scalable analytics solutions.
Proficiency in business intelligence tools (e.g., Tableau, Power BI) for creating dashboards and data visualizations.
Experience integrating AI/ML models to drive predictive insights and automate workflows is a strong advantage.
Skills
Strong technical acumen with the ability to design and implement advanced analytics and visualization solutions.
Exceptional analytical and problem-solving skills, with a focus on deriving actionable insights from complex datasets.
Excellent communication and stakeholder management skills, with the ability to translate technical insights into business impact.
Deep understanding of pricing strategies, customer success enablement, and revenue optimization principles.
Education
Bachelor s degree in Data Science, Computer Science, Business Analytics, Economics, Finance, or a related field. Advanced degrees or certifications in analytics, data science, or AI/ML are preferred.