Who it serves
- AI engineers
- Machine learning engineers
- Data scientists
- Emerging technical specialist roles
Roy Meshulam
AI & Advanced Data Learning & Development Director at Mastercard · Zurich, Switzerland
I build advanced, practitioner-level learning that helps AI engineers, machine learning engineers, data scientists, and technical specialists apply AI tools and practices more productively in real production environments.
AI & data learning
MLOps & LLMOps
Responsible AI
20+
Years of Experience
AI & Data
Advanced Learning
M.Sc.
Artificial Intelligence
Who Is Roy Meshulam?
Developing technical AI expertise through real systems, workflows, and production practice.
I'm Roy Meshulam, AI & Advanced Data Learning & Development Director at Mastercard in Zurich, Switzerland. I am an AI expert and technical learning leader focused on developing deep practitioner capability for AI engineers, machine learning engineers, data scientists, and emerging specialist roles.
I translate AI strategy and platform roadmaps into practical skill priorities, hands-on learning, and role-based progression. My work helps technical employees use AI tools more productively while learning how to build, deploy, monitor, debug, and govern AI and data systems at scale.
Before this role, I spent more than 20 years in software engineering, product delivery, and regulated financial services, from FX derivatives programs at UBS Investment Bank to Mastercard Agent Pay. That background keeps the learning I design grounded in how production systems are actually built and run.
Mastercard · Zurich, Switzerland · Since Sep 2026
Current Role: AI & Advanced Data Learning & Development Director
I own Mastercard's advanced AI and data learning strategy for its most technical roles. The work is deliberately scoped to advanced practice, not general AI literacy: turning enterprise AI strategy and platform roadmaps into the skills practitioners need to build, deploy, and govern AI systems in production.
What it covers
- Model development, evaluation, and iteration
- Data and feature pipelines
- Deployment, monitoring, and lifecycle management
- MLOps and LLMOps: reliability, performance, and cost
- Responsible AI, governance, and risk controls in practice
How it is built
- Progression across defined proficiency levels
- Hands-on labs, platform scenarios, and real failure modes
- Aligned with Mastercard’s AI and data platform direction
- Validated with senior AI, data, and engineering leaders
How success is measured
- Speed to production readiness
- Fewer repeat defects and less rework
- Consistency in how models are built, deployed, and governed
- Business impact, not participation metrics
What I'm Known For
Technical AI learning leadership, backed by engineering depth and years of shipping regulated financial technology.
Advancing technical AI capability
Helping AI engineers, ML engineers, data scientists, and specialist roles move between proficiency levels through hands-on learning tied to real tools and production workflows.
Turning AI strategy into practitioner skills
Translating AI and data platform roadmaps into skill priorities and learning investments, and retiring content that no longer reflects how the work is done.
Teaching from production experience
Grounding learning in more than 20 years of building software, payment products, and regulated systems, from FX derivatives at UBS to Mastercard Agent Pay.
Agentic commerce and fintech delivery
Scaling Agent Pay, digital wallets, and payment products across Europe by connecting engineering, product, and governance.
Career History
Current role
Mastercard · Zurich, Switzerland
AI & Advanced Data Learning & Development Director
Sep 2026 - Present
Building and sustaining deep, practitioner-level learning for Mastercard’s most technical roles: AI engineers, machine learning engineers, data scientists, and emerging specialist roles.
- Own the end-to-end advanced AI and data learning strategy, aligned with Mastercard’s AI and data platform direction.
- Translate enterprise AI strategy and platform roadmaps into skill priorities, learning investments, and sequencing decisions.
- Design progression mechanisms that help practitioners close the most common gaps between proficiency levels in real work.
- Build hands-on learning with labs, platform scenarios, and real failure modes, grounded in how teams ship, debug, and maintain AI systems.
- Lead through influence across Technology, Data, AI, and HR, and hold external learning partners to a high bar for technical depth and production realism.
Mastercard · Zurich, Switzerland
Product Delivery / Agentic Commerce Payments
Jan 2025 - Aug 2026
Led the European rollout of Agent Pay, connecting AI agents with secure tokenized payments for consumer and B2B commerce.
- Expanded Mastercard Agent Pay across Europe with issuers, acquirers, PSPs, and merchants.
- Embedded authentication, tokenization, and dispute resolution into agentic payment flows.
- Scaled transparent, controlled, and fraud-protected payment experiences for autonomous transactions.
Mastercard · Zurich, Switzerland
Product Delivery / E-Commerce Payments
Jan 2023 - Dec 2024
Drove go-to-market readiness and delivery execution for European e-commerce payment products using AI-driven analytics.
- Reduced launch delays by 20% by identifying readiness gaps through predictive insights.
- Improved customer retention by 15% through data-driven prioritization and customer scoping.
- Lifted launch efficiency by 25% with agile planning, automation, and predictive delivery practices.
Mastercard · Zurich, Switzerland
Product Delivery / Contactless Payments
Jan 2018 - Dec 2022
Led expansion of digital payments products including Apple Pay, Google Pay, and MDES for Device Wallets.
- Increased transaction volume and market penetration by 30% through data-informed rollout strategies.
- Raised product adoption and engagement by 20% through stronger positioning and messaging.
- Improved customer satisfaction by 25% while commercializing MDES for Device Wallets.
Mastercard · Zurich, Switzerland
Product Delivery / Masterpass
Jan 2015 - Dec 2017
Built stronger onboarding and implementation delivery for Masterpass through cross-functional execution and standardized delivery practices.
- Improved onboarding efficiency by 30% with a streamlined customer implementation process.
- Reduced project timelines by acting as the implementation subject matter expert.
- Increased customer satisfaction by 20% through better documentation, lessons learned, and process improvement.
UBS Investment Bank · Zurich, Switzerland
Software Engineer to Project Manager / FX Derivatives
Jul 2007 - Dec 2014
Progressed from software engineering into project management while delivering regulated trading systems and business-critical change.
- Delivered FX derivatives systems in C++, Java, JavaScript, and ActionScript with measurable gains in trading efficiency and accuracy.
- Achieved 100% on-time regulatory go-lives with zero customer disruptions across CFTC, MiFID, and ESMA-driven programs.
- Improved system performance, trading volume, and stakeholder satisfaction through structured execution and risk management.
Track Record
Outcomes from earlier roles across agentic commerce, digital payments, AI-enabled analytics, and regulated financial technology. This production and delivery experience shapes the learning I build today.
01
Mastercard | 2025 - 2026
Scaled agentic commerce payments across Europe
Led the expansion of Mastercard Agent Pay and brought secure tokenized payments into live agentic commerce journeys.
Impact: Unified authentication, tokenization, and dispute resolution in support of transparent, controlled autonomous transactions.
02
Mastercard | 2023 - 2024
Reduced launch risk across European e-commerce payments
Used AI-driven analytics to surface launch risk, sharpen prioritization, and improve market delivery across Europe.
Impact: Delivered 20% fewer launch delays, 15% stronger retention, and 25% better launch efficiency.
03
Mastercard | 2018 - 2022
Commercialized digital wallets and MDES products
Scaled digital wallet and contactless payment offerings through stronger positioning, execution, and product optimization.
Impact: Drove 30% transaction growth, 20% higher adoption, and 25% improvement in customer satisfaction.
04
Mastercard | 2015 - 2017
Simplified Masterpass onboarding and implementation
Standardized onboarding and delivery documentation to make implementations faster, cleaner, and more repeatable.
Impact: Raised onboarding efficiency by 30% and customer satisfaction by 20%.
05
UBS Investment Bank | 2007 - 2014
Delivered regulated FX technology under deadline pressure
Delivered business-critical trading and regulatory change programs under tight deadlines and strict compliance constraints.
Impact: Reached 100% on-time go-live dates with zero customer disruption while reducing project risk exposure.
Education
St. Louis, Missouri, USA
M.Sc. in Artificial Intelligence
Maryville University
Washington, DC, USA
Executive MBA
Quantic School of Business and Technology
Ramat Gan, Israel
M.Sc. in Computer Science
Bar-Ilan University
Ramat Gan, Israel
B.Sc. in Computer Science
Bar-Ilan University
Expertise
Advanced AI & Data Learning
Technical learning strategyRole-based proficiencyHands-on labsPlatform scenariosProficiency-level progressionAI workforce upskillingLearning portfolio managementLearning impact measurementLearning partner governanceCross-functional influence
AI and Data Systems
Artificial intelligenceGenerative AIMachine learningDeep learningModel evaluationData pipelinesMLOpsLLMOpsResponsible AIAI governanceReliability and performanceAI cost considerations
Financial Technology
Agentic commerceDigital paymentsTokenizationE-commerce paymentsAPI integrationRisk controlsPredictive analyticsData analysis
Product & Engineering
Product managementProduct strategyRoadmappingProduct launchAgile deliveryFeature prioritizationPythonJavaJavaScriptC++
Frequently Asked Questions About Roy Meshulam
Direct answers about my work, professional background, expertise, and contact details.
Who is Roy Meshulam?
Roy Meshulam is AI & Advanced Data Learning & Development Director at Mastercard, based in Zurich, Switzerland. He leads advanced AI and data learning for Mastercard’s technical practitioners, drawing on more than 20 years across software engineering, product delivery, agentic commerce, and regulated financial services.
What does Roy Meshulam do?
Roy Meshulam sets the advanced AI and data learning agenda for technical practitioners at Mastercard. He builds hands-on, production-relevant learning that helps AI engineers, machine learning engineers, data scientists, and specialist roles strengthen their skills and use AI tools more productively.
How does Roy Meshulam help employees build AI expertise?
He designs progression paths that help practitioners move between defined proficiency levels, using hands-on labs, platform scenarios, and real failure modes grounded in AI and data workflows. The focus includes model development and evaluation, data and feature pipelines, deployment and monitoring, MLOps, LLMOps, reliability, cost, and responsible AI.
What makes Roy Meshulam’s approach to AI learning different?
His work is deliberately scoped to advanced technical practice rather than general AI literacy. Learning is built around real tools, platforms, and constraints, and success is measured by indicators technical leaders care about, such as speed to production readiness, fewer repeat defects, and consistency in how models are built, deployed, and governed.
What is Roy Meshulam’s professional background?
Before his current role, Roy Meshulam spent more than 20 years across Mastercard and UBS Investment Bank. His background includes agentic commerce, e-commerce and contactless payments, digital wallets, FX derivatives technology, software engineering, and project management.
What are Roy Meshulam’s areas of expertise?
His expertise includes artificial intelligence, machine learning, advanced technical learning, MLOps, LLMOps, responsible AI, data and feature pipelines, AI governance, agentic commerce, digital payments, product delivery, and software engineering.
How can I contact Roy Meshulam?
Use the calendar link on this page to schedule a conversation, connect with Roy Meshulam on LinkedIn, or email him directly.
Where is Roy Meshulam based?
Roy Meshulam is based in Zurich, Switzerland, where he is AI & Advanced Data Learning & Development Director at Mastercard and has built his career across AI, fintech, and payments delivery.
Speaking, Advisory & Contact
Build deeper AI capability where technical work happens.
Available for conversations with leaders developing advanced AI practitioners. Topics I speak and advise on:
- Advanced AI and data practitioner development
- Production-relevant learning for technical teams
- AI engineering proficiency and career progression
- Measuring technical learning by production outcomes
- Production-ready AI in regulated environments
- Agentic commerce and digital payments
- Moving from engineering depth to product and AI leadership