#30 Paris Women in Machine Learning & Data Science: Ask Us Anything 🍹

We have been missing those informal moments chatting with our members at the end of our physical meetups, and have decided to organise a Zoom Apero “Ask Us Anything” for our last meetup of 2020! We were very happy and surprised by your number of questions! Here are some, grouped by category, with our answers:

1 — Transition

Until what age can a woman be datascientist?
Natalie Cernecka reflected on this question overnight, and came with the thoughtful linkedin post:

Coming from academia what are the biggest differences I should expect in the position in the industry? How to best approach a job search in the industry having only academic background? (type of positions: research engineer, machine learning engineer).
In machine learning & data science, academic background is valued 90% of the time! You should have a look at the requirements, and relate it to your work in academia. For example, did you deal with a package? Then you know how to code, and you know what quality entails, and so on. Also have a look at the current data science team: do people have a phd? Then you should be welcome! Best of the best: if you can contact directly someone in the team, s/he can explain in the details what the job title entails.

2 — Network

How to develop your network when you have a small team and you are an introvert?
You can find here a great guide of networking from Natalie! In a nutshell, networking is not about knowing very well-known people but know a couple of good people who appreciate you and your work, and can be your sponsor.

If you don’t want to go to an event and talk to strangers, you can also send a message on social media!

3 — Interviews & landing a job

What mistakes do people commonly make when preparing to DS/ML interviews? And at the interviews themselves?
During the technical test, don’t use technical stuff you don’t master! You might be asked to explain your choices, and this is what is key for most jobs. During other interviews, you should build a bridge between your knowledge and the company’s expectations, help them to see your value in their use case. And do prepare an introduction of yourself.

4 — Diversity

How can you attract diverse talents and show them that the company is inclusive?
BetterAllies and TheAllyance are sharing a lot of content about it. We discussed some ideas during this meeting, such as having photos of diverse people on your career pages, and training HR and managers.

Last point for this category, we would like to share with you this story from one of the attendees: About being emotional and masculine environment — just another experience. Yes, was very very emotional at least once (a lot of pressure to perform and a lot of personal things at the same time). What to do with it — I just asked for more time to do my tasks and be given a ¨room to breathe¨, not being pulled into meetings and corrections and critiques all the time.

5 — Learning

How to start learning about machine learning? And what resources for a beginner?
Chloé-Agathe wrote a great book that you can find here!
You can also visit websites such as machinelearningmastery.com, listen to twiml podcast (they are careful about diversity), and rely on newsletters. Podcasts and newsletters are great because the content is already curated and evaluated. Don’t push yourself too much, get to the real world!
Try a few things, and find your way: there is plenty of content, it depends on how you like to learn.

Finally we had one other question which does not find the categories above: “How can you join the WiMLDS Paris Slack?” ❤️. You can send a mail to paris@wimlds.org stating your request and the mail you want to be added with, and we will do so!

If you want to view the whole meetup, here is the youtube video:

If you want to keep posted about our activities, you are welcome to:

📑 check our Google spreadsheet if you want to speak 📣, host 💙, help 🌠

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📍join our Slack channel for more discussions about machine learning, data science, and diversity in tech!

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WiMLDS Paris is a community of women interested in Machine Learning & Data Science