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Interview with a Fellow: The Inspiring Story of Festo Owiny

We talked to Asigmo Fellow Festo, who has come a long way to find his passion for Natural Language Processing, about his experience in Asigmo, his background, and his future plans.

Asigmo: Hello Festo. Thank you for taking the time to talk to us today. Could you go ahead and introduce yourself? Where are you from, what have you done up until now and how did you end up in the Asigmo Data Science program?


Well, my name is Festo and I’m from Uganda. I worked for four years after my BSc, then went abroad for masters, and currently working as a data scientist. I landed in the Asigmo Data Science Program through my brother, a Mathematics PhD student who got the info through their forum. My application proceeded from observing the strong profiles of Asigmo trainers.

Asigmo: Could you tell me a bit more about your background?


My earlier childhood was quite challenging as I grew up in a small village in Northern Uganda that suffered from the brutal LRA rebel activity. Greatly inspired by our mother we always worked hard in school. Later, we joined our father in another region for safety and better education, who with great teaching abilities played a major role in my successes. He greatly empowered my mathematical skills and introduced me to chess and scrabble, prior to my joining competitive chess. Consequently, I developed dual passion in academics and sports, enjoying a successful academic and social track, with the initial dream of being a doctor. When I finished secondary school, I was among top three candidates in the final selection for a prestigious scholarship to study Computer Engineering in Japan. Shortly I was confirmed as the choice candidate and was advised to start learning Japanese, a language I would later use in the program. I had also received another scholarship to study Mechanical Engineering at Makerere University Kampala Uganda, a highly ranked University in Africa.

Unfortunately, I faced a very serious setback after being informally told that I wasn’t taken for the program of Japan, moreover I had already lost my Engineering offer at Makerere University. I felt devastated but after regaining myself I obtained another Scholarship to study Bachelor of Science in Mathematics, Physics and Computer Science at Makerere University. Upon completion I worked in a project of Ministry of Education for two years, implementing e-learning in secondary schools, here, I provided IT support and issued training to the stakeholders among other activities. Afterwards I joined banking as a credit officer. However, I always desired to study abroad, and after two years in banking I obtained a scholarship to study MSc in Computer Science at University of Trento Italy, specializing in Data Science. Despite the flexibility of this MSc program to diverse specializations, I chose data science given its match with my passion and skills. I was greatly fascinated by the applications of data science to address major industrial and societal challenges.

In addition, in my earlier career as a credit officer I always analyzed data to drive loan decisions, though with less sophisticated tools. Consequently, my decision to major in data science was quite obvious, also given my solid analytical foundation in chess. During this program I engaged in vast data science areas; NLP was my favorite. I also participated in several data science workshops and was a trainee with the iKernels Machine Learning group at the University.

After completion, I worked as a part-time machine learning engineer with a Nike distribution company in Verona, where I developed a recommender system, among other projects. Currently, I work as a data analyst/data scientist with The Classic Car Trust, Milan, since 2019. Here, I’m also responsible for the analytical content of “The Key”, a yearly publication.

Finally, my 2020 was packaged with the prestigious Asigmo program that dramatically altered the year pattern to productivity.

Asigmo: There's definitely a clear direction throughout your career that leads to Data Science. What were you expecting from the program? What was your main goal?


When I read the outstanding profiles and expertise of the program facilitators, I knew this would be a great opportunity to take. There’s tremendous benefit in interacting with experienced trainers. I was confident of being greatly enriched with diverse industry challenges and trending tools. "I saw this as a huge chance to get myself mentored by people who have already had profound impacts in the industry".

"I saw this as a huge chance to get myself mentored by people who have already had a profound impact in the industry"

Asigmo: Was there something that was surprising to you that you didn't expect from the program before you joined? Any particular tools or maybe other fellows and their perspectives on the same topic of data science?


Not really. Previously I worked with traditional machine learning methods, but I desired to improve my deep learning skills. I was very comfortable working with Python and the associated Machine Learning libraries. I've not had direct mentors in the data science field as I am solely responsible for the data science department. Oftentimes I initiated projects with the help of other department teams, and once the board consents, I carry on with the development of the system. Doubtless, the program was conducted by renowned academic and industry experts working across the full spectrum of data science. I got acquainted with leading methodologies and tools.

Asigmo: Were there any parts that were particularly challenging to you, as you mentioned, new tools, for example?


Not so, as most new skills were easily adaptable given my previous experiences. I wasn’t conversant with the deep learning libraries but quite easily I adapted given my comfort with machine learning tools. Perhaps, the major challenge I experienced was balancing this program with my job. It was very demanding but I was determined to learn too. Sometimes I had to sacrifice and work through the night in order to meet deadlines. Generally, the facilitators were very supportive.

Asigmo: How was your experience working in such a diverse team with that many different perspectives and career paths coming into the program?


A huge learning experience. If asked for a key quality that is of most value to me, I would reply “teamwork”. Teamwork makes the dreamwork, and diversity implies variety. The program attracted diverse talents, I really enjoyed working with the rest of the fellows. An incredible experience indeed.

"This program reawakened me to dream bigger than I've been, and also to take up stronger challenges that I've been taking."

Asigmo: Going into a slightly different direction, a more personal one. What pushed you to stay productive in such an unproductive and difficult year. How did you manage to overcome the struggles of this year?


Evaluating the year 2020, one of my greatest achievements was actually the Asigmo Program. This was a year of isolation, fear and potentially wasteful but the Asigmo atmosphere altered this pattern. My productivity centered on this program. We became one big family. We covered quite a lot in just a short time. Definitely a resourceful investment in one of the most challenging periods.

Asigmo: How did the skills that you learned in the Asigmo Program affect your current work? Was there anything that has changed?


A lot has changed. One of the most powerful things that this program provided was direction. That's really the essence of meeting experienced trainers. They point out learning paths, and it’s up to an individual to advance in a specialization. This program reawakened me to dream bigger than I've been, and also to take up stronger challenges than I've been taking. The path has been appropriately drawn by experienced trainers,now the challenge remains to continue learning and find new challenges.

Asigmo: Where do you think your near future will lead you to, do you have a dream job that you want to take up?


Absolutely. I would like to take up a Machine Learning engineer role, preferably in NLP. I worked on recommender systems and liked it too. My top choice is no doubt NLP and I’m always eager to learn the developments in this area.

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