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So you want to be a data scientist?
Misra Turp
23 episodes
5 days ago
Interviews with data scientists, data engineers, machine learning engineers and professionals in other relevant areas to data. We chat about how they ended up where they are now and what kind of projects they work on.
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All content for So you want to be a data scientist? is the property of Misra Turp and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Interviews with data scientists, data engineers, machine learning engineers and professionals in other relevant areas to data. We chat about how they ended up where they are now and what kind of projects they work on.
Show more...
Careers
Business
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#10 - An unexpected way of using data science and life at Adobe with Shivali Goel
So you want to be a data scientist?
23 minutes 51 seconds
5 years ago
#10 - An unexpected way of using data science and life at Adobe with Shivali Goel

Sometimes it’s hard to imagine a vast variety of jobs where data science skills and machine learning are used. So, we end up defaulting to a data scientist position. Shivali Goel’s job is an excellent example of a non-data scientist title where data science skills are highly used.

Shivali is a globalisation engineer at Adobe. She works on making sure that Adobe products are applicable and acceptable across the globe to different countries, cultures and languages. While doing so, she uses NLP and other ML techniques as her main tool.

This goes to show that you don’t only have to be a data scientist by title to be practicing data science and using the “cool” ML techniques in your work. 

Shivali says that her passion for languages, different cultures and NLP is combined in her position. Let’s hear it from her in this episode and go into the details of how she works.

So you want to be a data scientist?
Interviews with data scientists, data engineers, machine learning engineers and professionals in other relevant areas to data. We chat about how they ended up where they are now and what kind of projects they work on.