Mastercard Employee's Full Circle Journey: From Student to Mentor

I’m always interested in stories where better data leads directly to better decisions. This global business school had teams spending hours each week manually pulling reports from multiple systems. So insights were slow, inconsistent, and hard to act on. Ensono helped unify their data and removing 17 manual steps from reporting, moved from quarterly updates to always‑on insights and set themselves up for analytics and AI across the institution. It’s a strong example of how simplifying data access can free teams to focus on what really matters. Worth a read: https://okt.to/jIFc7b #DataDriven #AIReady #DigitalTransformation #Education #MakeBetterHappen

✨AI, Business & the Future of Work ✨ I’ve recently completed the course “AI, Business & the Future of Work” from Lund University, and it was a great opportunity to reflect on how Artificial Intelligence is already transforming our daily work with a meaningful impact on corporate business. During this course, I learned how IA refers to the ability of systems to learn from data, recognize patterns, and generate predictions or recommendations that support decision-making, transforming large volumes of data into faster, more accurate, and more strategic insights. Key applications include: - Automation of reconciliations and closing processes: AI can automatically match transactions, detect inconsistencies, and explain differences between systems. This significantly reduces manual effort and minimizes errors. - Automation of repetitive administrative processes: AI streamlines repetitive, rule-based tasks such as data extraction, data validation, report preparation, and manual postings. By reducing administrative work hours, finance teams gain time to focus on higher-value activities. - Predictive forecasting and scenario analysis: By learning from historical patterns and incorporating external variables, AI improves the accuracy of forecasts for revenues, costs, and cash flows. This allows finance teams to run faster, more reliable scenarios to support strategic decision-making. - Anomaly and risk detection: AI continuously monitors financial data to identify unusual transactions, fraud risks, or unexpected cost deviations, enabling finance teams to act proactively rather than reactively. - Market intelligence and economic predicted trend analysis: AI can process and analyze real-time economic and market data, such as macroeconomic indicators, industry trends, and pricing dynamics, to identify emerging patterns that may impact business performance. By transforming continuous market data into actionable insights, AI supports early identification of risks and growth opportunities, helping organizations anticipate trends, adjust strategies, and make more informed, complex, and visionary decisions. Aligning AI initiatives with long-term strategy and sustainability goals enables organizations to create value not only for shareholders but also for employees, customers, and society as a whole, driving long-term positive impact for both businesses and the planet. This is why moving toward AI is essential. It’s not a passing trend, it’s the future, and the moment to take action is now. 🚀 I’m very grateful to Santander Open Academy for this opportunity, which allows continuous learning and access to high-quality academic programs. 🎓 Excited to keep learning, evolving, and applying AI to create smarter, more sustainable finance processes that improve margins and drive stronger financial performance. #Finance #ArtificialIntelligence #AIinFinance #Sustaintability #FutureOfWork #ContinuousLearning #SantanderOpenAcademy #DataDrivenFinance

I’m always interested in stories where better data leads directly to better decisions. This global business school had teams spending hours each week manually pulling reports from multiple systems. So insights were slow, inconsistent, and hard to act on. Ensono helped unify their data and removing 17 manual steps from reporting, moved from quarterly updates to always‑on insights and set themselves up for analytics and AI across the institution. It’s a strong example of how simplifying data access can free teams to focus on what really matters. Worth a read: https://okt.to/gyBvxr #DataDriven #AIReady #DigitalTransformation #Education #MakeBetterHappen

At J-PAL North America, we believe data visualization is an essential component of designing and executing high-quality randomized evaluations. Catherine Darrow, Amanda Lee, Lisa Turley Smith, Jesse Gubb, and Caleb Smith—members of the J-PAL North America team working on the Learning Engineering Virtual Institute (LEVI)—were thrilled to join our partners at MC2 Education earlier this month for a training on data visualization in New Mexico. The training focused on using data visualization as a tool not just for analysis, but for effective communication with research partners, policy makers, implementers, and community members. Through hands-on sessions led by Stephanie Evergreen, we explored best practices for translating complex data into clear, actionable insights that support collaboration and decision-making. This trip also provided a valuable opportunity to strengthen our partnership with MC², which plays a critical role in supporting recruitment efforts for LEVI’s full-scale randomized evaluations. As LEVI teams move from pilots to full RCTs, close coordination between evaluation design, recruitment strategy, and partner communication is more important than ever. We’re grateful to MC² for the collaboration and thoughtful training, and we’re excited to continue working together to support rigorous, scalable evidence on AI-driven education tools. 🔗 Learn more about the LEVI partnership: https://lnkd.in/gGTRhCnR

"Out of 50 AI candidates, only 2 know our production tools." That's a senior AI project manager at a major Swiss bank talking about recruiting. The gap isn't about talent. It's about training. You've built impressive ML projects. You understand transformer architectures. You can explain gradient descent. But when the interview asks: "How would you design an agent system for mortgage processing that handles 50,000 applications monthly, integrates with legacy mainframes, and complies with Basel III and GDPR?" — academic coursework leaves you guessing. That's the gap the BAI Summer School closes. July 1-10, 2026 | Anglet, Basque Coast, France 10 intensive days building the agentic AI systems European banks actually deploy: • Multi-agent architectures for banking operations • Model Context Protocol integrations with live market data • Smart contracts on NEAR Protocol • LangChain orchestration for production environments • Compliance frameworks for regulated finance Faculty who've shipped production systems at UBS, BNP Paribas, Deutsche Bank. Not academics reading papers. Practitioners who understand both the technology and the organizational realities. Deliverables that open doors: Complete system architectures. Production code repositories. Capstone presentations solving real bank challenges. 4 ECTS credits + BAI Certificate. LinkedIn-ready portfolio. A cohort that becomes your network: Engineering students, MBA candidates, working professionals from European fintechs. The conversations that happen over 10 days of intensive collaboration don't happen in 90-minute lectures. Swipe through for the complete story → Applications open through May 15. University partner discounts available. Apply: https://baisummer.com Davy Cielen, Christian Hitz, Dr. Mario Gellrich, Alexander Walter, Karen Elliott, Alexandre MARTIN, Dean McKeown, Bruno Versaevel, Sophie Perrault, Renée Reijers, Jeannine Ameri Wanner, Prof Dr Ingrid Vasiliu-Feltes, DWARAKANATH AGARA RANGANATHARAO, Guillaume Dreyfuss, Stéphane Demarquette, Corina Taban, Saravanavel Subramanian, Jayshree Mallaya, Ismaelle Haddouzi, Cathal McCarthy, Sebastien BRISON, Yusuf Barman, Mihael Zivkovic #ProductionAI #AgenticSystems #Banking #FinTech #AIEducation #CareerDevelopment #ZHAW #EuropeanBanking

I’m always interested in stories where better data leads directly to better decisions. This global business school had teams spending hours each week manually pulling reports from multiple systems. So insights were slow, inconsistent, and hard to act on. Ensono helped unify their data and removing 17 manual steps from reporting, moved from quarterly updates to always‑on insights and set themselves up for analytics and AI across the institution. It’s a strong example of how simplifying data access can free teams to focus on what really matters. Worth a read: https://okt.to/I7PTUu #DataDriven #AIReady #DigitalTransformation #Education #MakeBetterHappen

I’m always interested in stories where better data leads directly to better decisions. This global business school had teams spending hours each week manually pulling reports from multiple systems. So insights were slow, inconsistent, and hard to act on. Ensono helped unify their data and removing 17 manual steps from reporting, moved from quarterly updates to always‑on insights and set themselves up for analytics and AI across the institution. It’s a strong example of how simplifying data access can free teams to focus on what really matters. Worth a read: https://okt.to/D7gube #DataDriven #AIReady #DigitalTransformation #Education #MakeBetterHappen

Day 3: Real-World Impact, Roadmaps, and the Future of Data 🚀📊 Day 3 has been about connecting the dots. It’s one thing to know "what" data is, but today was about seeing where it actually works and how to build a career around it. 🌍 Real-World Applications Data isn't just numbers; it’s the engine driving every industry in 2026: Healthcare: Predicting disease outbreaks and personalising patient treatments. Finance: Detecting fraud in real-time and automating credit scoring. Retail/E-commerce: Driving demand forecasting and hyper-personalized recommendations (think Amazon/Netflix). Smart Cities: Optimizing traffic flow and public resource allocation. 🗺️ My Learning Roadmap To master this, I’m following a structured path to ensure I don’t just learn tools, but build a problem-solving mindset: Foundations: Excel for data cleaning and basic statistics. Frontlines EduTech (FLM) #flm# #learningjourney#

Certification programs generate a wealth of data. Application trends, exam performance, renewal behavior, candidate engagement, operational timelines, support volume, and more. But too often, traditional reporting and BI tools turns that data into time-consuming exports, manual effort, and guesswork. No more jumping between tools to understand what’s happening in your results. Instead, imagine having a conversation with your certification data. Explore your data with Scout. And if you’re attending ATP Innovations in Testing 2026, come see it in action at our booth, #114. See what's waiting in your data ➡️ https://hubs.ly/Q043C53-0 #AI #InnovativeAI #AIReporting #CandidateData #ProgramData #CertificationManagement #Credentialing #Certification #CertificationProgram #Innovations2026 #AssessmentInnovation

The Data Mavericks Club at ASIST brings together students interested in data science, analytics, and emerging technologies. Through interactive sessions and collaborative learning, students develop skills to analyze information, solve problems, and create meaningful insights for real world applications. #DataMavericksClub #ASISTInnovation #DataScienceLearning #StudentClubs #AnalyticsInAction #FutureDataLeaders #TechEducation #ASISTCampus #HandsOnLearning