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Senior Analyst, Data Science & Value Optimization

Job in Washington, District of Columbia, 20022, USA
Listing for: National Science Teachers Association
Full Time position
Listed on 2026-07-16
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Business Systems & Technology Analysis, Data Scientist
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

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.
    • 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
  • Master’s degree in data science, Computer Science, Engineering, Mathematics, Statistics, Business Analytics, Economics, Finance, or a related field. Advanced degrees or certifications in analytics, data science, or AI/ML are preferred.
  • 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…
Position Requirements
10+ Years work experience
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