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The role of Tech communities in shaping your Data Science career

Catherine Gitau is a data scientist, a mentor, and a contributor to open source projects. A fascinating & hard-working lady leading the change in data science. We had a chance to hold an interview and she was kind enough to share with us her journey, lessons, strategies, and how she managed to leverage tech communities to develop her data science career.  

Enjoy the read!

Please tell us a little about yourself and how you got into the Data science space? 

I’m so glad we have this chance to connect! I did Mathematics and computer science as my undergrad course and I did it more for the math and not for the computer bit because I loved maths. Back in those days when one was doing such a course, the only career paths that were talked about were in IT, web development, or software engineering. I started with learning some web development and even built my portfolio site but I still felt like this space wasn’t for me.  During the Nairobi Tech Week conference in 2016, I attended a data science talk that sparked my interest. I started doing research and slowly started learning the tools needed to become a data scientist. I then joined the Nairobi Women in Machine Learning and Data Science community to find like-minded individuals and see what people are working on. During one of the talks, I approached Jessica Colaco the co-founder of Brave Venture Labs, and asked her if I could work for her as an intern in data science. I had done my background and saw that Chris Orwa, a well-known data scientist in Kenya works there and felt it would be a good place to begin my journey, so I shot my shot and I started working with Brave the following week and that’s where my journey began. 

How have tech communities impacted your Data Science career? What part did they play in shaping your career?

The tech community has played a huge role! From getting referred to job opportunities to enabling me to travel and attend international conferences, I have also made good friends from the community. I also believe that my contributions as a speaker in some of the meetups boosted my confidence not only in speaking in front of people but also my confidence in what I know as a data scientist. It’s one thing to speak to an audience but this opens up a space for open criticism and questions that will challenge your knowledge in the area.

Tech communities also challenged me to apply for my Masters’ in Machine Learning. While attending conferences I would speak to people who have done one or more Masters’ which motivated me to apply for one.

What role do you play in the tech communities?

1. I am a Mentor -  in addition to being experienced in my field, I am willing to share and help another person succeed. I gain the satisfaction of knowing that I have made a difference in someone’s life. 

2. A Speaker - I  volunteer to speak at some of the tech meetups organized by the tech communities locally, and internationally. 

3. Open source contributor - I have contributed to some of the projects worked on by community members, might not be in local communities but I’ve started being a very huge fan of open source projects which in turn helps me learn and helps others as well.

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How can one leverage the power of tech communities to develop a Data Science career?

1. Volunteer volunteer volunteer! I can’t stress that enough. If there’s a conference or talk coming up and they’re looking for volunteers, apply or volunteer to speak, help in logistics, etc. That way you become visible, you’ll interact with experts in the field.

2. Network as much as you can - get to know what people are doing, if they need help you can offer a hand and you’ll get to learn. You could even find someone to collaborate on a project with. 

3. Teach/Mentor others 

4. Be curious - ask as many questions as you can that will help you in your growth - Share your work to get instant feedback in the community through writing blogs - Contribute to open source work

What do you believe is the most exciting Data Science trend in 2021? 

More people coming together to work on African languages - I am in the Natural Language processing space, and I am happy to see people coming together to build technologies for our local African languages. A few years ago, this was non-existent.

The rise of DataOps/MLOps a methodology and practice that borrows from the DevOps framework which is often deployed in software development. It involves an end-to-end flow of data through an organization which removes obstacles that limit the usefulness or accessibility of data and deployment of data products. We see companies now coming up to hire for roles such as data engineers and data analysts to be able to build such products for the company. 

As a parting shot - What advice would you give to someone who wants to get into Data Science?

Recruitment in the tech space is community-driven, and making a career in tech or data science is much more than just sending a CV to get your next job, it’s all about personal branding.

Work on becoming a Visible expert in your field and get involved in the tech communities which will allow you to develop, grow and hone the skills that you would not otherwise find the time to do. Write and document your work, share it with people and communities to get feedback. Start writing blog posts talking about what you’ve learned or built. Share it with people to get feedback and this will accelerate your growth and if you are lucky someone will bump into it and offer you a job, you never know.

Connect with Catherine Gitau via Linkedin through this  Link