Says the leading author in Data Science. Here’s what they actually look for when hiring Data Scientists instead. — It might surprise you to hear that most business leaders who hire Data Scientists don’t actually care about fancy statistical/ML algorithms you might have read or learned. Certainly, it seems counter-intuitive based on opinion of aspiring data hopefuls that you must have complex, state-of-the-art algorithms under your technical tool-kit.

Perfect scores can no longer get you a Data Science job in current economy. Here’s why. — I have been active in the job hunt for about 3 months now, and after 8 final interviews, 20+ technical interviews, and dozens of first rounds, I’ve come to realize a strange phenomenon in the current job market: acing the final interviews can’t guarantee a data science job. For background…

2 common pitfalls of aspiring Data Scientists, and how you can avoid them through these simple ways. — Interviewer: Haebichan Jung, Interviewer at TowardsDataScience.com. Interviewee: Amit Jain Tech Lead, ML at Trade Rev. For more TDS-only interview, please check out here: Tds Interview - Towards Data Science Read writing about Tds Interview in Towards Data Science. A Medium publication sharing concepts, ideas, and codes.towardsdatascience.com

TDS interviews AI visionary on her cutting-edge research at Google Brain, how Deep Reinforcement Learning works, and more. — Interviewer: Haebichan Jung, Project Lead at TowardsDataScience.com. Interviewee: Azalia Mirhoseini, Ph.D., Tech Lead and Senior Research Scientist at Google Brain. One of the “35 innovators/visionaries under 35” by MIT Review. This interview took place at Toronto Machine Learning Summit (TMLS) on November 2019.

12 tips for getting back on your feet after your (many) falls during the job process. — You’ve been applying to Data Science positions nonstop. …

Real world is not a data competition — here are 3 reasons why. — Major thanks to Rachael and Will from Kaggle for reviewing and providing recommendations on this article. TLDR: Kaggle competitions are great for Machine Learning education. But it can set wrong expectations about what to expect in real-life business setting. …

How we overestimate the role of Data Science projects in the job process — and the 4 interviewing skills that actually matter. — TLDR: Stop pursuing projects if you want to be a Data Scientist, and focus on mastering these four skills first. Outline 1. The Problem: How we overvalue the role of projects in the Data Science hiring process. 2. The Anecdote: How my own Data Science project went viral online, but had little payoff during actual interviews.

One of the Core Developers of Scikit-learn shares 3 practical ML techniques every data scientist needs to know. — Interviewer: Haebichan Jung, Project Lead at TowardsDataScience.com. Data Scientist at Recurly, SF. Interviewee: Andreas Muller, Core Developer of Scikit-learn. Author of the O’Reilly book Introduction to Machine Learning with Python. Research Scientist and Lecturer at the Data Science Institute at Columbia University.

Help us craft interview questions for high-profile speakers at the TDS-partnered AI Conference. — In less than 2 weeks, TDS will be at the Toronto ML Annual Conference as the Official Media Partner and video host. During the conference, we will interview internal speakers with exquisite resumes on pressing data science issues — face-to-face! …