Long-term volunteer Sukhil Patel
“I get to meet so many interesting charities and understand a lot about the work they’re doing.”
Pronouns He/him
Roles Data scientist/Machine learning engineer at Kaluza
Committee member, Data Ambassador, and everything in between at DataKind UK!
Links LinkedIn
This month we meet Sukh, who has been a volunteer with us for around five years. We’re really proud to say that he’s been inspired by the community to find a role in green energy today. He’s also been a superstar volunteer in almost every role that we have, and is a fantastic advocate of DataKind, even bringing his own brother on to a project.
What is your data background?
I studied maths at university and when I left, scrambled to get the first job I could find, as many do! That ended up being a general tech consulting role with a software called SAP.
I still wanted to use my problem-solving and maths skills. An opportunity that was more data science-focused came up at a large car company. The role involved survival analysis and the likelihood of someone buying a car — although normally survival analysis is a bit more morbid and not about getting a new car!
That’s when I first started working with data and using R, and I really enjoyed it. I liked having the ability to predict, validate predictions, run A/B tests and see them work, and see there was truth to what I was doing.
What kinds of data projects do you currently do?
I currently work as a data scientist and/or machine learning engineer at Kaluza (named after a German physicist who supposedly figured out the fifth dimension) where I work on control and optimisation software for high electricity usage devices like electric vehicles and heat pumps.
The software is supposed to help optimise control and charging of things like electric vehicles so that energy is consumed when it’s best for the grid, and when when less carbon can be used to produce that energy. This means managing the demand for energy so it’s cheaper, greener and easier for the grid to handle.
How can you intelligently control devices to reduce costs and balance energy supply, so that coal and gas plants don’t have to turn on to help manage energy demand, and help to manage costs too? There’s optimism that the use of electronic devices is on the rise and this sort of tech will be more prevalent. It’s very interesting.
What drew you to volunteer with DataKind UK?
Previously, I enjoyed my work, but not the application of it on cars and marketing. But I wasn’t sure how to make the jump. My brother was working for mental health charity Mind at the time, and said it would be interesting to apply what I was in doing to his work.
I decided I wanted to start an organisation to help charities to do data science projects. But I knew nothing about the space, so I did a quick search, found DataKind UK, and thought ‘oh, this is brilliant!’
I did my first DataDive weekend about four years ago, with the charity Lancashire Women. I got to meet so many people whose roles were varied across sectors. I started thinking about sectors I had a passion for and areas I cared about, including healthcare and energy. Luckily, I found this small start-up looking for a junior data scientist, and was able to get the job.
I’m thankful to DataKind for a lot — for opening my eyes to what’s out there! That first weekend I met people in neuroscience, healthcare, consulting in different companies, doing all sorts of stuff. DataKind helped me in a couple of different ways: first through networking and finding a group of amazing people that helped me understand that there’s all types of jobs out there. And secondly, upskilling. DataKind is the perfect safe space to upskill and have a positive impact at the same time. You gain a bit more confidence, learn a lot from those weekends, and it helped me with the transition and search for that new job.
What do you wish you’d known when you started to get into data?
You will never know everything: there will always be a new tool, technique, or method you are unfamiliar with. Data science is particularly fast-moving. It’s more important to keep that curiosity and eagerness to learn. You don’t have to learn everything up front in order to get a job or help with a project.
Everything is also learnable. You can be a specialist but it doesn’t mean you will know about another area. Talking to people, sharing that knowledge, and asking what they do is really useful. People are generally quite happy to talk about what they do, even if you don’t get hands-on experience. It’s good to know what you might move into and it’s always refreshing to hear about something new. Sometimes whole new areas open up to me because I learned the name of a new technique, then that leads to five new things.
I think everyone is in the same boat — no one knows everything. Be okay with that. You’ll feel less anxiety in general!
What is a data project that inspires you?
An external project run by a small organisation doing great work called Open Climate Fix. They are a not for profit research group trying to use computers to fight climate change. They thought there was an opportunity to improve solar forecasting at a national level, to find out how much solar energy is generated at any given time in the UK. If you can know that number and be as prepared as possible, you don’t have to keep as many fossil fuel-based power plants on standby.
They use short-term forecasting called solar nowcasting and take different inputs such as cloud movements, plus inputs from older models for weather prediction. It’s cutting-edge stuff for a very nice use case, some great impact — and it’s open source so anyone can contribute!
Did you always think you were going to go into data? If not, what else?
Leaving university I wasn’t thinking about a job in data per se — I was still figuring things out. I wanted to do something quantitative, but wasn’t sure what. I didn’t have the skills to go straight into it, and it wasn’t on my radar until I had my first opportunity with it, then it opened my eyes to the career. I still enjoy being hands-on with quantitative data work!
What surprised you about your volunteering experience?
DataKind helped widen my understanding of what’s out there. That’s why I enjoy working with them so much — I get to meet so many interesting charities and understand a lot about the work they’re doing. You don’t normally get that level of access or insight. A lot of it is about understanding service users, understanding the outcomes and impact — I really like to see that work.
I introduced DataKind to my brother’s branch of Mind in Hackney and Waltham Forest. He came to the DataDive weekend, loved it, then took the initiative and learned R through DataKind. He’s now adata manager in a legal aid charity, and is using R all the time.
I’m continuously on the lookout, when I hear about charities, to see if DataKind could help them. I recommend it to anyone I meet, so hopefully I’ll get a few more charities through the pipeline! I love volunteering there: I’ve been a troubleshooter multiple times, a Data Ambassador a couple of times, a DataDiver at weekends, helped at ‘Are You DataDive Ready?’ sessions, and I was on a committee for a bit. The Scoping and Impact Committee was one of my favourite roles, seeing the early stages of what a charity wants, refining that, and also hearing about interesting ideas that can’t make it into a project, or considering ethical implications.
You also get to call the charity and hear about what they’ve done after a project. It always puts a smile on my face to hear them say: ‘We went to DataKind, we ended up publishing this whole report, doing a lot more research, we got loads more funding, and that all started with this weekend.’ It’s brilliant work you do!
Is there a resource you’d recommend to the community?
There are two YouTube channels I love that do a great job explaining a lot of the theory in statistics/data science/machine learning: 3blue1brown and StatQuest. Both do a great job at demystifying complex topics in data science and stats, useful for newcomers and veterans alike!
Tell us something completely non-data-related about yourself!
Jobs like this, you sit in front of a computer a lot of the time, so most of my hobbies are trying to get away from computers and screens. I recently walked 100km of the West Highland Way in Scotland which was stunning and I’m planning to do a cycling trip from Dunkirk to Amsterdam later in the year. You definitely need time outside to get the blood pumping to balance out a not-so-physically-active career!
