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 Amardeep:

I work with organisations to drive innovation through trusted data. This requires striking the balance between securing and protecting data and making it available for analysis, AI, experimentation and personalisation.

Ultimately this means that we can trust our employees are using data in line with our mission, our employees can trust the data they are using and our customers can trust that we are using their data appropriately, fairly and ethically. Data trust empowers people to use data creatively to uncover insights, make informed decisions and ultimately deliver on business strategy.

How did you start out in your tech career?

I’ve always worked closely with data. My background is in Physics at Cambridge and Harvard, and my academic research was analysing seismic datasets to model the Earth’s inner core. It was incredible that these raw lists of numbers could be translated into understanding the inner workings of the planet.

I continued to apply my data skills working internationally building valuation models for the financial industry with Oliver Wyman. I wanted to experience working for myself, and set up a science education company working with schools across London. Working with teenagers certainly allowed me to develop skills engaging difficult audiences with challenging content!

I love teaching, but felt limited by the scale of impact. I could also see that the classroom was being transformed by data and technology; and moved into data trust.

Data is a huge enabler, the number of people you can potentially impact is huge. This is incredibly exciting. However, with this power we have a responsibility to ensure that this impact is positive, ethical and aligned to our mission and values. We can only achieve positive impact if we can trust our data.

What are the signs of success in your field?

If people use the data!

If we can make trusted data available across organisations – we can realise great potential: empowering our people to experiment, research, innovate, develop creative analytics, uncover insights and drive decision making. I usually come into organisations that are struggling with data quality challenges. Often people feel that they can’t find the data they need, and when they find it they aren’t sure they can trust the numbers , resulting in friction and frustration.

A sign of success is a sustainable, scalable data trust framework that people adopt and continue to engage with, enabling trusted data, driving innovation and positive impact.

What is the best and worst thing about your job role?

The best thing is being able to work with a wide range of people across organisations – from execs to analysts. Data touches everybody, which makes data trust very social. People really care about these challenges. Everybody wants to do work that matters and data trust directly influences the quality of their work and nature of impact they can have.

I enjoy working together to design new ways of working that drive trusted data and enable innovation.

The worst thing is dealing with negative misconceptions and prejudices around data governance. Some people can be hostile based on their previous experience – which may have been overly bureaucratic with lots of rules and meetings. This can be overcome, it just takes some time to understand the root of these perceptions.

What can you advise someone just starting out to be successful?

Maintain a broad perspective – it can be very easy to become siloed without realising. Go to events like London Data Science Festival and chat to people – understand their challenges and how tech helps. I really enjoy connecting with people who work in data – they are usually friendly, generous and happy to share their experience.

How do you switch off?

Playing with our two year old is a great way of switching off. I also really enjoy theatre – performing improvisation and comedy. Stepping on stage and playing is a great way of getting away from the screen and switching off.

What advice would you give your younger self?

Be comfortable with the uncertainty and not having the answer.

What is next for you?

I hope to continue driving trust in data and enabling organisations to realise the huge potential of their data assets.

If you could do anything now, what would you do? Why?

I’ve always wanted to travel overland from here to Punjab – to connect where I grew up and where my family are from, to see the places in between and experience the transition. I’ve managed to do parts of the journey, but never end-to-end.

What are your top 5 predictions in tech for the next 10 years?

This is a very exciting time in data trust! The field is evolving and developing quickly to support new opportunities offered by technologies such as AI.

  1. Data trust as competitive differentiator: As technologies become more commoditized, trusted data will emerge as a critical competitive advantage. Organizations that prioritize foundational data management and integrate data activities into job descriptions will realise significant value.
  2. Responsible AI as business imperative: There will be heightened focus on explainability and transparency in AI decision-making, particularly as it is increasingly integrated in high-stakes areas like healthcare and justice. Ethical AI standards will be embedded in development lifecycles including mitigating bias in data collection and analysis. Customers will hold companies accountable for appropriate and ethical data practices.
  3. Augmented Data management: AI and ML will be increasingly integrated into data management.Automation will enhance data integration, quality assurance, and governance, protecting sensitive data while enabling access.
  4. Regulatory evolution and compliance: The regulatory landscape around data usage, AI deployment, and ethics will continue to evolve and mature globally. Governments will enact and refine regulations to address concerns related to data privacy, bias mitigation, and AI ethics. Expect more regulatory enforcement actions based on AI/ML decisions.
  5. Accelerating data literacy and democratisation: Users across organisations will be empowered with self-service tools, democratising access to data and enabling immediate insights, collaboration, and innovation. Gen AI will facilitate natural language querying of data to uncover insights.

Watch Deep’s session at DSF here.

Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!

Want to become a DSF Speaker? Apply here!