As we return to one of Europe’s leading data innovation hubs for a unique edition of Data Demystified Summit Berlin, we’re delighted to feature Huy Tran, Head of the Data Science Chapter at Tamara, in our Amazing Speaker Interview series. A former mathematician turned data leader, Huy blends statistical rigour with a passion for clarity, education, and impact. At this year’s summit, he will join the Panel Discussion | [AI & Customer Experience] Advanced Analytics, MLOps & Responsible AI for Customer Engagement, where he will share how his team operationalises AI responsibly while building a culture of experimentation and transparency across the organisation.
The Data Demystified Summit Berlin will be held alongside The MarTech Summit Berlin at the JW Marriott Berlin on 5 March 2026! Maximise your organisation’s learning potential with our exclusive Dual Summit Pass, which allows free movement between both summits and access to all sessions.
About Tamara
Tamara is a leading Saudi-based fintech platform offering buy now, pay later (BNPL) solutions across the Middle East. By combining cutting-edge technology with a customer-first mindset, Tamara empowers users to shop with flexibility while helping merchants grow. With a growing focus on responsible AI and data innovation, Tamara is shaping the future of digital commerce in the region.
Quick Q&A with Huy Tran
Could you start by introducing yourself and your current role at Tamara?
I’m the Head of the Data Science Chapter at Tamara. My role focuses on evangelising the effective use of AI, machine learning, and data insights across the company by setting best practices for data science and experimentation, sharing practical insights, and organising knowledge-sharing sessions across the organisation.
What are some ways your team uses AI or MLOps to deliver real-time customer insights or next-best-action strategies?
We place strong emphasis on business understanding, data meaning, and statistical rigor. Two team members, one machine learning engineer and one data scientist, have built robust tooling to monitor data quality and model performance. This helps us to quickly catch any data drift problem. Many teams (PMs, Product Designers, Commercial, Customer Experience, etc.) are using an internal AI data-assistant tool to help them with data insights. As a company, we are still early in our journey, so a key focus is building a stronger experimental culture, data-quality awareness, and statistical thinking to support reliable real-time decision-making.
Based on your experience, what practical steps can companies take to operationalise AI responsibly across marketing or product teams?
The most important step is to lead by example; the person leading the team must genuinely use data and AI in their own decision-making. Beyond that, companies need to invest in a clear, well-structured data foundation with shared definitions, metrics, documentation, and standards. Responsible AI ultimately comes from clarity, transparency, and continuous monitoring.
You mentioned dreaming of building something wonderful for the world(on LinkedIn). What motivates you in your work today, and how do you bring that vision into your role as a data leader?
Every morning before work, I tell my kids, “I’ll help someone work better today. Wish me luck.” Then at dinner, I usually tell them what interesting things I did at work. What motivates me is helping people think more clearly and reason better with data. Seeing that “aha” moment, when someone gains a new perspective, is incredibly meaningful. I bring this mindset into my role by focusing not only on building systems but also on education, clarity, and learning together.
Looking ahead to 2026, can you share one personal or professional goal you’d like to achieve?
I’d like to give at least three talks at universities in Saudi Arabia, to show students that science and data are both beautiful and useful.
Huy’s thoughtful approach to leadership, from building data assistant tools to guiding teams with curiosity and statistical discipline, demonstrates that responsible AI is not just about models—it’s about mindset. Whether he’s helping colleagues think more clearly or inspiring the next generation of data scientists, Huy is committed to making AI accessible, meaningful, and human. We’re excited to welcome him to Data Demystified Summit Berlin 2026, where his insights will resonate with anyone navigating the evolving intersection of customer engagement, data quality, and ethical AI.
Join Us Now!
The Data Demystified Summit series aims to bring together the best minds in the data field from a range of industries through diverse and engaging formats. This in-person event promises a full day of networking, bringing together over 150 professionals for an English-speaking regional summit. The summit will feature dynamic formats such as Panel Discussions, Keynote Presentations, Fireside Chats, and Lightning Talks, ensuring the most comprehensive summit experience. Seize this opportunity to learn from top industry experts, share ideas with peers, and engage in in-depth discussions with professionals from diverse sectors. Bring your team, and get ready for 2026!
We are looking forward to meeting you in Berlin on 5 March 2026!
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Last updated: January 2026
