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Turing College provides learners with an opportunity to get even more insights and perspectives about data science and analytics industry through 1-1 sessions with industry professionals. It is also a great way to gain some useful contacts for your professional network.

 

How are these meetings different from other 1-1's?

  • The meetings will happen with mentors that are not Turing College STLs or Turing College staff. Instead, these will be volunteers from various well-known companies and institutions. Some examples: Google, Tesla, Waymo, Unity, GetJar, Microsoft, Harvard, Oxford. More are to come, as we are constantly searching for even more mentors.

  • We place more emphasis on meeting multiple different people so that you can get as many viewpoints from different companies in different countries. Therefore, by default, we expect learners to talk to different mentors in each subsequent session (new registration will be necessary). However, if you feel that talking with a particular mentor was really useful and you would like to meet them more than once - let us know.

  • The structure of these meetings is flexible. You are encouraged to discover which topics are the most interesting to you when talking to a specific mentor. We also provide some sample questions to help you start the conversations.

 

What to do if you're interested?

  • Choose 2 mentors from this page that you would be interested have a talk with. You will get assigned one mentor out of those two, preferably the one you listed as your first option.

  • Fill in this form and indicate your first and second priorities.

  • Based on the number of learners interested, you will either get an industry professional assigned immediately and informed of the next steps or will be put on a waiting list and informed of it.

 

Who can join?

Every learner at Turing College can express their interest in attending the meetings. However, only those who have initiated the endorsement process will be permitted to participate. Also, since mentor time is limited, if there are more learners interested than there are open slots, the sessions will be prioritized for people who are close to the beginning of their job search.

Sample questions you might want to ask during these meetings

  • What do you think is the most important thing to know for a junior in this industry?

  • In your experience, what were some of the biggest cultural differences between different companies/countries that you had to adapt to?

  • What is your personal idea of a good path to learn data science?

  • How would you solve technical problem X (could be problems from projects in your course)?

  • What does it take to get employed at Y?

  • What are the most recent developments in the industry that I should follow?

  • What soft skills have you found to be most useful in your career? Do you have suggestions on how to develop these skills?

Mentors

Povilas Gudžius

https://www.linkedin.com/in/gudzius/

AI/ML Technology Specialist @ Bloomberg in NYC. Expertise in Computer Vision, NLP, and Alternative Data applications in Finance. Working with NYC Hedge Funds and Silicon Valley tech firms. 12 years in FinTech and 5th year as PhD researcher at VU DMSTI, Cognitive Computing Group. His recent work on Deep Learning-based object recognition in Satellite Imagery was nominated as one of the top papers in 2021 by the LT AI Association. Feel free to reach him with any questions related to Data Science in Finance and HealthTech, alternative data, wearables, and IoT sensors.

Maynk Yadav

https://www.linkedin.com/in/maynk-y-bb0731b/

Maynk is working as Technical Program Manager at Google. Over the last 11+ years Maynk has worked across different industries such as Technology, Pharmaceuticals, Fast-Moving Consumer Goods, Consumer Healthcare and Biopharmaceuticals wherein he has gained experience in supply chain, operations management, demand forecasting, process development & improvement, system implementation and project management. He is currently working in the global network planning & design team at Google where his work focuses on managing large scale cross-functional projects. Maynk has an educational background in engineering and business management. He will help you on both technical (based on experience) as well as non-technical topics by leveraging his own journey and past experiences.

Dalia Jankevičiūtė

https://www.linkedin.com/in/dalia-jankeviciute-a4b6b569/

(Unavailable during 2022 autumn sessions)

She's been in Google for over 5 years and founded Women@Baltics chapter as well as currently leading Women@CEE; coached over 520 professionals and 40 facilitators in 7 countries on self promoting skills whilst being an ambassador of women and underrepresented groups empowering program #IamRemarkable. Dalia is a professional coach, specializing in career and motivation coaching and is looking forward to helping you navigate the next chapter of your career.

Deividas Matačiūnas

https://www.linkedin.com/in/deividas-mataciunas/

Deividas Matačiūnas is a highly experienced professional in the field of data and AI. He currently serves as a Board member of the AI association of Lithuania and holds the position of Data Lead at telecommunications company Sunrise in Switzerland. In addition, he is the CEO of the AI consultation company "AI connections." With over 6 years of experience in data, Deividas specializes in building machine learning and deep learning models to help companies achieve their AI goals. He is particularly passionate about large language models and speech applications. Deividas built various AI models for the Lithuanian language in his free time.

Peter Klemens Grafe

https://www.linkedin.com/in/ped-grafe

Data Scientist at Tesla, Co-Founder of Low Heat Collective and ProgramEURs. He has a background in economics and business analytics graduating from the Rotterdam School of Business (RSM). He can help you understand the working culture at Tesla and dive into required skill sets.

Mike Jin

https://www.linkedin.com/in/mike-jin-13993b39/

Mike Jin is a Preceptor in the Stem Cell and Regenerative Biology department at Harvard University and Machine Learning Engineer at Centaur Labs.  Prior to starting his current roles, Mike has worked on projects ranging from designing and building data services (Microsoft), to finding cancer genes using biological network data (Dana Farber Cancer Institute), to developing an at-home COVID testing device (Wyss Institute), to building inference tools for classifying and enriching bank transaction data (Heron Data).  Mike holds a Ph.D.

from Harvard in Systems Biology, where he studied molecular computing and developed a DNA-based molecular recorder and accompanying inference framework.  He recognizes the value in having diverse interests and exploration, as well as the importance of crafting an understanding from time to time of one's past experiences in the context of one's future goals.  Mike has always made teaching and mentoring a priority, most recently having taught an intensive integrated science course to Harvard College students for three years, mentored and provided college counseling for high school students in the Minds Matter Boston program, and served as an academic tutor and research mentor for students at the Research Science Institute.  He currently teaches courses in data science, therapeutics, and biotechnology to MS/MBA joint degree students at Harvard Business School, and looks forward to helping Turing College learners in whatever way he can, whether it be lending an attentive ear to learning frustrations, discussing interview mindsets and strategies, or talking about academic interests.

Renaldas Zioma

https://www.linkedin.com/in/renaldas/

Renaldas combines Machine Learning with experience in Computer Graphics and Game Development at Unity Technologies. He leads research into neural representations and advises the cross-platform neural network inference engine. In the past he brought Unity engine to mobile platforms and made AAA console games at Electronic Arts.


Romanas Zontovičius

https://www.linkedin.com/in/romanasz/

Romanas Zontovičius is a Director of Innovation Department at Kaunas Science and Technology Park. Fot the last 10 years Romanas worked for various IT companies in Silicon Valley (San Francisco Bay Area, USA): 7 years with GetJar, one the most successful Lithuanian startups. He did Sales and Sales Operations and was a primary contact for many key clients such as Facebook, Google, Amazon, Zynga, Rovio, eBay, and many other app developers. He was VP of Mobile Sales at Spigot Inc. When at Nextury Ventures Romanas mentored portfolio startups, help them get into various acceleration programs in US, and was their agent in Silicon Valley. For the last 2 years Romanas worked with Waymo, a former Google’s autonomous vehicles project, as a lecturer/senior instructor where he taught classes for the current and future safety drivers as well as future safety instructors.

Anshu Jalan

https://www.linkedin.com/in/anshu-jalan

(Web3 course learners)

Anshu Jalan is a Software Engineer who has been involved in web3 since 2018. He is currently handling smart contracts and backend design at Plenty Network, a prominent trading platform on Tezos blockchain. In his journey, he has worked on a broad spectrum of web3 applications, ranging from derivatives trading protocol to NFT based games. 

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