TechKnowledgical Sarin Devraj, Avi Ahuja, Anish Sharma

In Episode 2 of Season 2, we break down one of the most requested episodes: a day in the life of a machine learning engineer.  

Hear from Tomasz Jurczyk, Machine Learning Engineer at Moveworks, about how he broke into the field and the types of problems he solves on a daily basis. From creating algorithms to understand human language no matter how complex, to creating a knowledge graph on enterprise support, Tomasz knows it all.

Follow us on social! 

Twitter: https://twitter.com/techknowledgpod​​​/

​LinkedIn: https://www.linkedin.com/company/techknowledgical/

Instagram: https://www.instagram.com/tech.knowledgical/

Website: https://anchor.fm/techknowledgical

In the first episode back for Season 2, we talk to Connie Yang, Lead Data Scientist at Pallet.  

Connie transitioned form an Applied Math & Computer Science degree at Carnegie Mellon into an entry-level Data Scientist role at Microsoft. During her time at Microsoft, she cofounded a Women in Data Science Community and grew as a leader and people manager.  Finally and most currently, she made the switch to the startup world as Lead Data Scientist at Pallet. 

Learn how Connie grew in her role and the things she did to set herself up to become a leader in her field!  

Use YouTube? Subscribe: https://www.youtube.com/channel/UCpBrr_8wDDf93CvEQ3IRkNQ

Follow us on social! 

Twitter: https://twitter.com/techknowledgpod​​​/

​LinkedIn: https://www.linkedin.com/company/techknowledgical

Instagram: https://www.instagram.com/tech.knowledgical

Website: https://anchor.fm/techknowledgical​

In this episode we talk to Alex Carmen about her experience and knowledge working in presales at IBM and transition to post sales working in customer success at Mulesoft. We discuss what each role represents at the two companies, day to day responsibilities of someone in sales, the differences between pre and post sales, and finally how Alex first got her start into the world of tech after studying chemistry.  

00:00 Intro 

01:34 Finding interest in tech with a chemistry + economics degree 

08:35 IBM sales interview process & skills needed 

10:55 Impact of your role & environment on your personality 

15:25 Summit Program & sales training at IBM 

18:18 Roles & responsibilities as an Account Executive 

21:11 Learning about new industries 

24:11 Diving deep  on sales terms & processes 

28:47 Jumping from IBM to MuleSoft 

32:08 Account Executive vs. Customer Success Manager 

35:57 Diversity, Equity, Inclusion work throughout Alex’s life 

41:39 Closing advice on getting into sales or customer success

Shardul is a writer, marketer and generally curious cool cat. He currently works as the Creator Marketing Lead at Public where he's in charge of all things creators on the platform. Public is on a mission to make the stock market more inclusive, educational and fun. You can join public for free and get your free slice of stock at http://share.public.com/shardul.  Shardul also writes a great newsletter on the creator economy news and does deep dives on creators at http://creatorsdigest.substack.com.  

In this episode, we dive into: 

0:00 Intro 

4:02 Switching from Software Engineering to Product Marketing 

7:32 Experience in PMM at Salesforce 

12:26 What is Creator Marketing & How Shardul Moved Over 

19:24 Most Interesting Creators Out There 

26:23 Becoming a Creator Himself & Going to Public 

34:13 Creator Marketing at Public 

42:25 Advice for Creators 

46:52 What’s Next for Shardul

In this episode we chat with Gabi Campagna Lanning about her vast experience working in user research and design at Big Tech (Google, IBM) and a few startups along the way. She takes us through her education (undergrad in Architecture and MS in Fine Arts), how she first got into user research, and ultimately her experience and thought process for thinking about designing for some of the world’s most complex enterprise Machine Learning products.   

00:00 

Intro 02:11 

Interviewing for UX Research Roles 

04:35 Deciding to get a Master’s Degree 

08:57 How to build your portfolio 

14:45 Why did you choose IBM for design? 

17:22 Where do UX Researchers fit into the product cycle? 

22:30 How do you truly empathize with users? 

27:31 UX Research career ladder 

31:00 Differences between IBM and startups 

33:50 UX Research at Google 

36:00 Closing thoughts

Andrew Dabydeen studied Operations Research & Engineering for his Bachelor's at Cornell University — with a heavy curriculum towards statistics and computer science. Post-undergrad, he decided to get consulting experience at Accenture. After gaining a breadth of experience across multiple industries and seeing various roles in the data space, he pursued his Masters in Data Science at Brown.

Since Brown, Andrew has worked at Shutterstock and is now currently a Data Scientist at Peloton. In this episode, you'll hear Andrew go deep on:

0:00 Intro

1:10 Thinking About Careers at Cornell

2:50 Time at Accenture

6:12 Deciding What to Do Next

8:57 Choosing MS in Data Science at Brown

12:14 What’s the MS in Data Science at Brown like?

15:15 Recruiting into Data Science

18:37 Interviewing at Companies in Different Stages

21:29 Biggest Piece of Advice in Interview Process

24:13 Day-to-day as a Data Scientist

26:30 How do Data Scientists Prioritize Work?

28:23 Data Science Stakeholders

30:17 Career Progression

33:56 What is Machine Learning Engineering?

36:10 Is a PhD the only way to get into machine learning engineering?

38:39 Actionable Advice for Learning Data Science

41:35 Closing Thoughts from Andrew