Mastercard
Financial Services
SeniorAnalyst,DataScience&ValueOptimization
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optimal for Senior candidates.
“Senior Analyst, Data Science & Value Optimization at Mastercard. Skills: Data Science, Value Optimization, Business Intelligence, Automation. Design value enablement frameworks. Implement value enablement frameworks”
What You'll Achieve.
Enhance value delivery; Support scalable solutions; Align with Mastercard's growth objectives; Deliver impactful insights; Drive customer success; Drive revenue success; Quantify and communicate value; Drive decision-making; Enhance accuracy and efficiency; Enable data-driven customer engagements; Empower customers with actionable insights; Empower internal teams with actionable insights; Ensure alignment with revenue goals; Maximize customer outcomes; Improve efficiency and impact
Industry & Context.
Problem solver; Actionable insights
In the office 3 times per week
What They're Looking For.
Must Have
Master's degree in data science, Computer Science, Engineering, Mathematics, Statistics, Business Analytics, Economics, Finance, or a related field, 5+ years of experience in analytics, data science, pricing strategy, customer success, or related roles, Proven track record of developing and scaling data-driven tools and frameworks with measurable outcomes, Expertise in programming (Python, R, SQL), Experience building scalable analytics solutions, Proficiency in business intelligence tools, Technical acumen with the ability to design and implement advanced analytics and visualization solutions, Exceptional analytical and problem-solving skills, Deep understanding of pricing strategies, customer success enablement, and revenue optimization principles
Nice to Have
Advanced degrees or certifications in analytics, data science, or AI/ML, Experience integrating AI/ML models to drive predictive insights and automate workflows, Experience in the payments, financial services, or technology sectors
What You'll Do.
Design value enablement frameworks
Implement value enablement frameworks
Support initiatives across Pricing
Align solutions with Mastercard's growth strategies
Collaborate with global and regional stakeholders
Ensure consistency and scalability of solutions
Tailor approaches to regional nuances
Provide data-driven recommendations to optimize pricing strategies
Enhance pre-sales propositions
Ensure customer success
Develop advanced analytics tools
Deploy ROI calculators
Deploy value dashboards
Quantify value to clients
Communicate value to clients
Utilize programming languages for data analysis
Utilize programming languages for modelling
Utilize programming languages for tool development
Leverage business intelligence platforms
Create dynamic dashboards
Create data visualizations
Drive automation and scalability
Integrate AI/ML models
Integrate advanced analytics
Enhance accuracy of tools and insights
Enhance efficiency of tools and insights
Build frameworks to measure customer value realization
Build frameworks to track customer value realization
Enable data-driven customer engagements
Partner with cross-functional teams
Design tailored customer solutions
Design business cases
Integrate predictive models
Integrate real-time insights
Develop self-service analytics tools
Empower customers with actionable insights
Empower internal teams with actionable insights
Identify opportunities for revenue assurance
Implement opportunities for revenue assurance
Identify opportunities for revenue optimization
Implement opportunities for revenue optimization
Monitor performance metrics
Analyse performance metrics
Ensure alignment with revenue goals
Identify areas for improvement
Drive post-sale optimization efforts
Develop tools that track realized ROI
Provide diagnostics to maximize customer outcomes
Work closely with cross-functional teams
Foster a collaborative and innovative environment
Encourage knowledge sharing
Encourage adoption of technical best practices
Support training for internal teams
Support enablement for internal teams
How You'll Work.
Team & Collaboration
Global and regional stakeholders; Cross-functional teams; Sales, Product, Finance, Customer Success
Communication Scope
Translate technical insights; Business impact communication
Full Job Description
**Our Purpose** _Mastercard powers economies and empowers people in 200 + countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential._ **Title and Summary** ### Senior Analyst, Data Science & Value Optimization ### The Senior Analyst, Data Science & Value 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 Mastercard's 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. • L
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