As a data scientist, you are not only expected to know your expected values but also your expected runtime. Do you know basic computer science concepts like Big-O, standard data structures, and basic algorithms? Do you think about edge cases and test your code? Worry not! In this session, CDSS will go over important concepts you should know, walk through real interview questions, and share some tips regarding coding.

Data science interviews often test your SQL skills, so to prepare you, CDSS is going to walk through everything you need to know to ace it! We'll start from basic SQL syntax and work our way up to more advaned functions, as well as walk through the approach to some typical interview questions.

Time: Thursday 10/18, 7:30 - 8:30 PM
Place: Barnard 302

Slides: https://github.com/jillianknoll/SQLinterviews

So, you want to be a data scientist, but how fast can you answer this question?

If I have two decks of cards each with half blue cards and half green cards, should I draw from the deck of 10 or 100 to maximize the probability of drawing two green cards in a row in the first two draws?

Did it take you longer than you would like? No worries, CDSS has you covered! Technical interviews for data science positions are notorious for throwing hardball statistics questions at you to test not only your math skills, but also your ability to think under pressure. :scream: At Probability and Statistics for Interviews, CDSS will walk you through a repeatable process of figuring out the right answer for these kinds of questions. Whether you’re a math wizard or are taking your first probability class, come to our event for an hour of fun and collaborative problem solving!

When : Thursday, November 9 at 8:00pm to 9:00pm

Where : Pupin 214

For more information and RSVP

Slides: bit.ly/ProbStatsInterviewFall2017

What even is a data science interview? Do they want me to be a developer, or an analyst, or a unicorn? At this workshop we’ll go over what to expect in data science interviews, focusing especially on in-person tech interviews. From the basic layout to the right answer to (almost) every “what data structure can you use to make this faster” question, you’ll be ready to land the internship or job of your data-science-filled dreams.

Chris Mulligan is currently a Quantitative Researcher at Two Sigma Investments, LP. He builds models to make predictions of financial markets using untraditional data, which is a sentence he never imagined he’d say about himself. Prior to Two Sigma, Chris interned at Kickstarter, Facebook, and The New York Times, and before that, he spent 7 years in political data analysis and modeling, most recently as Director of Analytics at YouGov. Chris received BA and MA degrees in computer science and statistics from Columbia in 2015, where he was a TA for COMS3157 AP and STAT4400 StatML and cofounded CDSS.

Slides: bit.ly/2yt3aD7