Data Science Interviews with Nick Singh

For an episode all about tips for crushing interviews for Data Scientist roles, our guest is Nick Singh — author of the bestselling "Ace the Data Science Interview" book and creator of the DataLemur SQL interview platform.

Nick:
• Co-authored “Ace the Data Science Interview”, an interview-question guide that has sold over 16,000 copies since it was released last year.
• Created the DataLemur platform for interactively practicing interview questions involving SQL queries.
• Worked as a software engineer at Facebook, Google, and Microsoft.
• Holds a BS in engineering from the University of Virginia.

Today's episode is ideal for folks who are looking to land a data science job for the first time, level-up into a more senior data science role, or perhaps land a data science gig at a new firm.

In this episode, Nick details:
• His top tips for success in data science interviews.
• Common misconceptions about data science interviews.
• How to become comfortable with self-promotion and increase your chances of landing your dream job.
• Strategies for when interviewers ask if you have any questions for them.
• The subject areas and skills you should master before heading into a data science interview.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

The 20% of Analytics Driving 80% of ROI

Today’s episode is with freakin' David Langer, people!! (So obviously it's brilliant, witty, and full of laughs.) He fills us in on the most powerful 20% of analytics — the analytics that drive 80% of companies’ return on investment.

Publishing under his Dave on Data brand, Dave's YouTube channel is top-notch, with several videos that have over a million views (and the thumbnails are hilarious; check 'em out). He is an exceptionally accomplished data scientist and software engineer, including spending nearly a decade at Microsoft's Global HQ, where his titles included principal software architect, principal data scientist, and director of analytics.

Topics in the episode include:

• Surprisingly powerful modeling approaches in spreadsheet tools like Excel

• The SQL databases we'll need if the data sets we're working with are too big for spreadsheets

• Why R programming is easy and should be our default language choice for moderate to advanced statistical analysis

• How companies can maximize value from machine learning

Listen or watch here.