Speaker Spotlight – Daria Meshcherina

Hi! I’m Daria. I have been doing applied research and Data Science in a very diverse set of industries: financial markets, hedge funds, music industry and insurance. Working in large corporations as part of larger teams, or in small start-ups very hands on, I always find it fascinating how Machine Learning tools can uncover patterns that can not be found by other means. I also love translating those into real business results, showing the tangible value Data Science can bring.

How did you start out in your tech career?

I moved to Data Science from more traditional research, adding coding skills and python on top of my statistics and econometrics knowledge. I did a 3 months bootcamp, and an end-to-end data science project as part of it, and it helped a lot to gain confidence and also have something demonstratable for the interviews.

What are the signs of success in your field?

I think there are a lot of expectations packed into Data Science. You should be good at coding and engineering, as well as have a solid mathematical and statistical background, and then marry it all with a deep understanding of your business domain so that you can solve relevant business issues and deliver commercial value. If you can find that sweet spot using both technical expertise to solve problems and soft skills to communicate the results to less technical audience, that’s what I think delivers most impressive results in the end.

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

As a Staff Data Scientist, I still get to do a lot of hands-on projects and prototyping, which I really enjoy. At the same time it’s hard to balance it with management and strategy, and context switching between these modes of operation is quite tough.

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

Try to understand what your strengths are, where your interests lie, and then develop yourself and your career on the intersection of both. The field is too vast to try and chase expertise in everything, you might as well play to your strengths and enjoy the process.

How do you switch off?

I actually have a constant stream of ever changing hobbies! But there is always some physical sport, and something more artistic and crafty to switch up my activities. My latest obsessions are commercial dancing, and I’m part of a sea shanties choir!

What advice would you give your younger self?

I would say to try as many things as you can, and trust your intuition. If you can honestly reflect on how much you enjoy different types of work and projects, you might get to where you want to be and where you belong even faster.

What is next for you?

Part of why I like Data Science and Machine Learning is that there is a constantly expanding amount of things to learn, growing faster than you can possibly keep up with it. It would be nice to keep working on new fascinating projects and keep learning more, and I also want to continue helping others build their career in this field.

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

I was always curious about human biology, there is something very transcendental about it. If I could, I would explore the cross-section between Machine Learning and medicine, and explore novel clinical applications of existing algorithms.

What are your top 4 predictions in tech for the next 5 years?

I have a few hopes on where we go (whether we get there or not is another question!)

1. I hope we shift en masse from using AI to harness operational efficiencies to more efficient and scalable ideation and prototyping

2. We would break a plateau in LLM capabilities by shifting from using more data to creating models that learn better from existing data

3. I wish we shifted attention from commercial applications of AI and ML to ethics and governance. We could use the LLMs and its existing biases as a mirror of the current state of the world and underlying data and design next iterations based on where we want to be, not where we are.

4. We should not impose traits of humanity and human intellect on AI. Even if it reaches the levels of AGI and sentience in our lifetime, it would do so without the biological and cultural constraints and context that humanity had to struggle with. We should instead cultivate the mindset that it will be a completely different type of intelligence, without our evolutionary baggage.

Watch Daria’s session at the Data Science Festival here.

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

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