How to Start a Career in ML: Some Scientific Food for Thought.
Alexander Anikin, 2017| Align Technology, Senior Machine Learning Engineer
Meet Alexander Anikin, Skoltech graduate and a true expert in Machine Learning engineering who went from being an intern at Yandex to finding ML applications in the real world. In this story, Alexander talks about his experience and gives advice to all Skoltech students. Enjoy!
why Skoltech?

Before Skoltech I've worked as a business analyst at Deloitte. Although I graduated from the mechanics & maths department of MSU, I didn't feel like I was using my full potential at my current job. So, I've decided that switching fields of study is the best way to go. Skoltech was the best option for that.

The second reason is I have never seen such a great team of lecturers and TA's in any other university. The faculty at Skoltech had experience in almost everything, from teaching cutting-edge things at foreign universities to working with real companies successfully applying their research. This was impressive and the approach of learning when you are getting fundamentals within direct applications into life seemed the most perfect for me.

Last but not least, with Skoltech I was able to leave my job and fully go through studies without needing to work and study simultaneously.

what was your career path?
After the first year of my master's degree I joined Yandex' autonomous cars project as a part of a summer internship. This experience gave me a huge boost in skills that got me started on my path.

At the very end of my 2nd year at Skoltech I joined Qiwi Bank as a Leading Data Scientist. I worked on developing of classical ML models from scratch for prediction of conversion on requests for one of their credit products, finding target auditory and recommendations of the next purchases for POS-active clients.

Soon after I joined Align as a Senior Machine Learning engineer, working mostly with analysis of dental images (classification, detection, instance segmentation tasks). In a few months I became a Team Lead having a group of 3 developers and 1 QA engineer. However, after successful launch of a project which lasted for more than 2 years, I decided that people management (which became an essential part of my job) required too much emotional power. So I pursued a career in a more technical direction, and now I'm an Expert ML Engineer, technically leading couple of projects and working on deep learning applications for 3D mesh data analysis and fusion of different data sources (2d with 3d). I'm also responsible for generation & challenging of scope and approaches for solutions of different problems which I share with my teammates. From a technical standpoint I'm not only working on native research building models and new approaches but also responsible for wrapping those models into services for launching into production, also I'm actively contributing into our internal machine learning platform developing custom libraries and tools to ease our work.

During my studies at Skoltech we've tried to convert our scientific study into a startup related to automation of recyclable waste sorting process, but didn't succeed mostly due to the very unfriendly environment in the garbage collection business in Russia. Another attempt was my two friends and I tried to launch a startup based on application of deep learning in the field of retail, but after about 1 year of work we decided to switch to our major jobs as it was moving very slowly and outcomes were not clear at that point. However, these were great learning experiences that helped me to understand more about what I want to pursue in my career.
what does your typical day look like?
I have a bit shifted schedule as we're working closely with teams located in the US (which is good since I love my business trips to California and North Carolina!), so my working day starts around 11am and lasts typically till 8pm.

The work/life balance is close to perfect, there is no significant overworking and friendly atmosphere. We're trying to follow the best practices of agile, having many teambuilding activities like stand-ups, weekly sync-ups, sprints & retros etc.

Data Science
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how do you apply what you learned at Skoltech?
Actually I can say that my current job is directly following up on what I've learned at Skoltech. I've started with applications of deep learning to image processing which was a primary subject for me at Skoltech and now extended knowledge to 3D data processing, so I won't be able to do anything of that without what I've learned for my master's degree. And what is more exciting for me is that now my work has lots of research, just like it was during studies.

Another important aspect is leadership & soft skills which I've learned from different projects at Skoltech and now applying it almost everyday. The most important skills for me are the ability to have my own independent opinion despite the authority of other people and not being afraid to propose it, the ability to meet consistent challenging ideas and approaches to come up with the best solution, the ability to ask correct questions and change mindset to something more global than just your local tasks, ability to present and defend your ideas.
and now about Skoltech
We are Skoltech – a new international English-speaking STEM university that was founded by the group of world-renowned scientists in 2011 in Moscow, Russia. In just 8 years, we united dozens of researchers and globally renowned professors, built a stunning campus, set up world-class labs and made it to the top 100 young universities in the Nature Index. Read more >>
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