Influencing data science without data science
By trade, he’s not a data scientist, nor is he a machine learning engineer. What’s more, you may also notice that his Linkedin profile credentials don’t relate to STEM at all. So you’re probably wondering, how has Ravit Jain has become a prominent figure in the data science space?
We’ve got all the answers for you!
There is a common assumption that an influencer in the data science community will have a specific type of background. Whether it be a job title or degree qualification.
However, Ravit renders this assumption irrelevant by completely crushing this stereotype. His illustrious career proves that some areas commonly overlooked in data science should be given the recognition it deserves.
Join Ravit as he speaks about the unique role he plays within the data science community.
Huifang: Based on your LinkedIn profile, you’ve had experiences in the Finance and Investment Banking sector, as well as marketing. But I know you through Data Science! With such a varied background, can you tell me how you’ve gotten here?
Ravit: I did my MBA in finance, so that’s where my background lies. This gave me experience working with numbers.
Working with accounts and spending time on excel is the coolest job in the world if you’re interested in it. But I found that it really wasn’t my thing. I believe that conducting research is more suitable for me. It gives me an opportunity to play around with numbers to create reports for market research. At this time my role was to explore data at an early stage.
Then Packt happened to me. It was very interesting to see the book publishing world where it’s a different ball game altogether. It’s a thriving real business where authors come on board to put pen to paper. I started marketing books about data science, AI, cybersecurity and programming.
I started meeting really interesting people because of the books and I love talking to people! So eventually, I became a part of the community as I couldn’t get enough of helping others.
Huifang: Tell us more about what personal branding means to you, a phenomenon that started from “The Ravit Show”.
Ravit: The whole thing about personal branding is understanding your purpose. It takes time but depending on how much you talk about it, it will eventually happen.
When I started “The Ravit Show” around 10 months back, my purpose was to create a platform for my community where it benefits my guest speakers as well as the audience.
Knowing my audience well and what they want, I invited data experts who make strides in the community to my LinkedIn and YouTube live show. My audiences are free to ask questions and get firsthand answers from senior members of the data science world. Chief officers of companies who are interested in ramping up their products and services also get that visibility through my live show.
While growing together as a community, I’ve successfully created a brand for myself where people know they can get quality content.
Huifang: What tips do you have for those that want to create a personal brand?
Ravit: Always be consistent in what you’re doing. Do not forget your evolutionary purpose and remember to post at least two times a day.
Huifang: Did “The Ravit Show” spin-off from the needs of your day job at Packt? Do share with us your journey in growing the community.
Ravit: No, I didn’t start “The Ravit Show” because of Packt. It actually started because of the pandemic. I felt that I should do something helpful and free for the community.
I don’t always call all my authors on the show, but it’s important for specific topics to be explored properly. It creates a dialogue between the audience and the author. It also gives the author a platform to explain certain parts of their work.
I wouldn’t say I understood what my audience wanted in the first few weeks. I need to actively take care of those who attend my show. I try to understand what they do, speak with them and get feedback on what they like about the show.
It’s not about just hosting something and feeling that you’re doing the right things. We need to go out there and understand what the audience wants.
I have partnered with DATAcated by Kate Strachnyi, the Data Science Infinity by Andrew Jones, Business Science by Matt Dancho, Learn Data Engineering by Andreas and my show sponsor 365 Data Science to share these free courses.
You can follow “The Ravit Show” on LinkedIn and Twitter, subscribe to its YouTube channel or even join the Ravit Slack community.
Huifang: How do you normally choose your speakers?
Ravit: At the beginning, I had shortlisted 50 people that I wanted to reach out to. It was a struggle trying to book their calendars and get started. Out of that 50, I have interviewed 15 at this point.
Since then, there have been another 10 people that have reached out to me to showcase their products and services.
I try to understand and think about the needs of the community before I get them on board to talk more about it. I had to pick a relevant topic to talk about.
The idea is to stay relevant, stay consistent and help the audience.
Topics such as data storytelling are never out. Its styles vary from person to person. From Kate Strachnyi, Brent Dykes to Kirk Borne, everyone has different ways of understanding data storytelling.
Data literacy is also one of the most important topics trending right now. We are living in a world of data. We have sent and received data by picking up a phone or chatting online, even on LinkedIn for instance. How much of it are we aware of? Why not be data literal about the things we do?
Huifang: What are your roles with Packt then?
Ravit: I’m a community manager at Packt Publishing and I work closely with the world-class authors who make strides in their writing for us.
I bridge the gap between the communities and amplify their books at a global level, making sure their resources reach the right communities.
For instance, I know that there’s an NLP (Natural language processing) community that would be interested in books on transformers. So, by sharing Denis Rothman’s first book on transformers with my community of 30,000 followers, I would be able to get their feedback on it. This way, I’d be bridging the gap between Packt and the community.
Huifang: What other channels have you been using to bridge this gap before LinkedIn?
Ravit: With the impact of Covid-19, things have changed. People are more active on LinkedIn and the virtual conference circuit in general.
LinkedIn gives a personal touch, letting people know that you can reach out to a human.
On LinkedIn, people are at ease with things I post. Knowing that they can always post questions or email me directly for enquiries is reassuring. However, we are still reading articles from websites because they are still the number one source of information.
So, we are continuing the traditional ways of collaborating with third-party websites like InfoQ, TechForge and KDnuggets to have interviews, book recommendations and articles excerpts.
I used to go out and get speaking engagements for our authors in conferences around the world. Sometimes, these opportunities are limited by our physical bandwidth. But everything’s virtual today. So, if there’s a conference happening today in San Francisco, I can easily ask my author to speak there because it’s all virtual.
Huifang: Could you name the top 5 most memorable guests that you have interacted with?
Ravit: I can never say exactly as my guests have spoken on completely different things and each of them is a master in their field.
If I have to name someone, Kate Strachnyi is like a leader and a mentor to me. I’ve known her for more than two years now and she inaugurated “The Ravit Show”. Being the first guest on the show, she spoke about her inspiring journey to creating DATAcated for learning. I’ve learnt from her in terms of helping the community.
Help everyone in your journey, because you are part of everyone else’s journey.
I also remembered a great session with Ken Jee, a sports analyst. He’s a great guy who makes fantastic data science courses and videos for his YouTube channel.
There is Gilbert Eijkelenboom, the author of “People Skills for Analytical Thinkers”. He spoke about how we think and he explained human gestures in the show. It was fun because it was a little different.
Another favourite is Robert Sutor, the Chief Quantum Exponent at IBM. He has written a book for us, published by Packt — “Dancing with Qubits: How quantum computing works and how it can change the world”. He shared insights about quantum computing in layman terms to benefit people like me, who didn’t know how it works.
The other ones I remember are Thom Ives, who I call father in the community, and Danny Ma. I love talking to them. We had a late night with a 90 minutes session but Danny was so kind to stay back and answered every question that the audience had. It was a huge achievement for me to have Danny launch his courses on “The Ravit Show”!
(Huifang: I asked for five and Ravit gave six and he has more on his list, trust me.)
I listed these because you’ve asked, but having invested all my heart and soul into each interview, I really liked each guest who has been there. They have always been kind in explaining the smallest things to the community.
Huifang: The data science community is very close-knit and there are many platforms for resource sharing. What distinguishes your platform from the rest?
Ravit: There are many communities such as my Ravit’s Community, Danny’s Data with Danny, Alexey Grigorev’s DataTalks.Club on Slack and we are in each other’s community. The data science community is big. So the Slack community allows those coming to us to be in one place and be there for each other.
These Slack channels help people be on a page where they can interact with less talking and more work exposure.
Different people in the community can share different resources in the Slack channel which is useful to different people within the community. This is helpful for the community to gain knowledge. Also, it is easier for us to get in touch with anyone in the community.
There are no differentiating factors between the Slack communities unless they are more into the technical stuff.
For instance, Danny’s audience might be a little different from mine in terms of the courses that he has created and the context he wants in his community. He is more technical, so people can direct their questions to him if needed.
I’m just the guru who shares resources and helps you connect to the right people.
I’m not a technical guy but I have the right folks in the channel who can ask each other questions. My channel is open for everyone to share their work and get recognition in the community.
So there you have it! Impacting data science with no maths involved. To influence data science without data science, simply start by getting involved and being helpful.