Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!
A bit about Rajat:
Rajat Kumar is an accomplished analytics leader with over 8 years of experience in Retail Consulting and Customer Science. Currently serving as an Applied Data Science Manager at dunnhumby, Rajat leads Customer Engagement and Media workstreams across North and Latin American retailers, operating at the intersection of Strategy, AI, and Data Science.
His expertise spans Pricing & Promotion, Category Management, Retail Media, Customer Engagement, and New Business Development, with a global footprint across Retail, Pharma, Sports, and QSR sectors. Rajat holds an MBA from the Department of Business Economics, University of Delhi, and brings a multidisciplinary foundation in Statistics, Economics, Finance, and Management.
With a deep interest in economic trends and policy, Rajat enjoys reading and writing about economic phenomena in his free time. He is known for driving innovation, operational efficiency, and leading high-impact projects while mentoring dynamic teams of data scientists and developers.
How did you start out in your tech career?
I began my career with dunnhumby itself, starting in the Customer Science and Retail Consulting space, where I was deeply fascinated by how data can remove ambiguity from real-world decision-making. My early work focused on building data science models for customer engagement, campaign setup, and personalisation, after which I broadened my experience across key areas of retail analytics including pricing and promotion, category management, and customer knowledge.
This journey ultimately led me to dunnhumby’s retail media programmes, where I now lead the Applied Data Science efforts for our North and Central American clients – bringing together analytical rigour, commercial understanding, and product-focused thinking to drive meaningful impact at scale.
What are the signs of success in your field?
Success in the data science field is reflected in the ability to create meaningful, measurable impact – using analytics to influence decisions, solve real business problems, and deliver tangible value. It shows up when solutions are not only scientifically sound but are trusted, adopted, and scaled across teams. Strong cross-functional collaboration, clarity in communicating complex ideas, and the ability to translate insights into action are equally important markers of maturity. Finally, continuous learning, adaptability to evolving technologies, and building capabilities that uplift the wider organisation all signal a data scientist who is not just delivering outputs, but shaping long-term, sustainable success.
What is the best and worst thing about your job role?
The best part of my role is the impact – using data to bring clarity to complex problems and see that translate into real business results. The toughest part is balancing that impact with the ambiguity that comes with evolving priorities, where you often have to make decisions even when the data or context isn’t fully complete.
What can you advise someone just starting out to be successful?
- Build a decision muscle, not just models. Ask “who will use this and how?” – then design for that path.
- Ship small, learn fast. Move from notebooks to repeatable modules; measure impact early.
- Own the narrative. Great science needs story and visuals; make outcomes legible to non-experts.
- Automate the boring stuff. Free your time for novelty – codify, template, and push standard work to platforms.
- Focus on craft and community. Share cases, mentor, and engage with forums like DSF – your network amplifies your work
How do you switch off?
Switching off for me means reconnecting with the things that ground me. I love spending unhurried time with my family, which instantly resets my mind. Whenever possible, I take short trips to the mountains – there’s something about fresh air and quiet views that helps me slow down and recalibrate. And when I’m home, I usually turn to reading and a bit of spiritual practice, both of which help me reflect, unwind, and come back with a clearer, calmer perspective.
What advice would you give your younger self?
I would tell my younger self to trust the journey a little more. Every experience – whether it looked like a breakthrough or a setback – was quietly shaping the clarity, resilience, and purpose I have today. Stay curious, stay grounded, and don’t rush to have all the answers. The right opportunities always arrive when you’re consistently learning, showing up with integrity, and backing yourself with confidence. And most importantly, enjoy the process a bit more – growth happens even when you don’t notice it.
What is next for you?
What’s next for me is a blend of growth, curiosity, and carving space for things that matter.
Career-wise, I’m excited to keep expanding the impact of data science in areas where it meaningfully shapes decisions – driving deeper adoption, scaling our retail media and customer engagement capabilities, and stepping into more strategic, cross-market leadership responsibilities. Personally, I want to stay intentional about balance: spending more time with family, travelling to places that inspire me, and continuing my journey with reading and spirituality. I’m at a stage where learning, purpose, and well-being feel equally important, and the next chapter for me is about growing in all three dimensions with a bit more clarity and a lot more gratitude.
If you could do anything now, career-wise or personally what would you do? Why?
If I could do anything right now, I’d love to teach – to share what I’ve learned to bring clarity, drive impact, and make better decisions. Teaching has a way of grounding you, reminding you of first principles, and helping you grow through others’ curiosity. It’s something that gives me energy and a sense of purpose beyond day-to-day work.
What are your top 5 predictions in tech for the next 5 years?
First, AI will move from being a tool to becoming a trusted thinking partner, deeply embedded in daily workflows and decision-making across industries. Second, data will become truly autonomous – with pipelines that self-heal, models that self-optimise, and systems that continuously learn with minimal human intervention. Third, personalisation will finally reach “segment-of-one” at scale, powered by real-time data, multi-touch attribution, and unified identity systems. Fourth, the divide between product, engineering, and data science will narrow, giving rise to cross-functional “fusion teams” that build and deploy solutions end-to-end with unprecedented speed. And finally, ethical, explainable, and responsible AI will become a non-negotiable standard, not just for compliance, but as a competitive differentiator – with organisations winning based on trust, transparency, and the ability to deploy AI safely at scale.Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!Want to become a DSF Speaker? Apply here!