CDSS X Dataiku: Data for Improved Cities (TechTalk + Recruiting!)
Apr
18
7:30 PM19:30

CDSS X Dataiku: Data for Improved Cities (TechTalk + Recruiting!)

When: Wednesday, April 18 2018 @ 7:30pm - 9:00pm

Where: Pupin 329, Columbia University

CDSS is hosting our last data science tech talk of the semester with Dataiku! Dataiku’s core product is a complete data science software tool aimed at shortening the time-consuming load-clean-train-test-deploy cycles of building predictive applications. The French-based startup scored a $28 milion Series B investment in late 2017, a super cool office space in downtown Manhattan, and is currently hiring!

At this event, Dataiku’s Lead Data Scientist, Jed Dougherty, will present a project analyzing the largest national dataset on evictions from Kansas City using Dataiku’s platform. Jed will also speak about the full-time and internship opportunities available at Dataiku.

Please RSVP to the event if you can.

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Foursquare Tech Talk and Q&A
Apr
11
7:30 PM19:30

Foursquare Tech Talk and Q&A

For more info.

About:
Since launching in 2009, Foursquare has collected 12 billion global check-ins, which have formed the cornerstone of its location intelligence. Using this data, Foursquare is able to detect a billion new place visits per month via the activity generated by users and business partners around the world. Foursquare now offers its proprietary location technology to hundreds of other companies, including Apple, Samsung, Microsoft, Twitter and AirBnB.

We will give an overview of Foursquare's data and how it has evolved, starting with the check-in and expanding to include continuously-detected visits on millions of smartphones. We will also describe Foursquare's core location technology, Pilgrim, how it works, and some of the data science challenges it has generated.

Speaker:
Adam Waksman is the Director of Engineering and Data Science at Foursquare, with oversight over Pilgrim. He has worked in various startup areas, including healthcare technology, fintech, and locations intelligence. Most notably, he was Chief Technology Officer at Epickk and was a day-one member at Arcesium. Prior to that he earned his Ph.D. at Columbia University; his academic papers in computer science and neuroscience have resulted in close to a thousand citations.

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Financial Literacy
Apr
4
7:30 PM19:30

Financial Literacy

When: Wednesday, April 4 2018 @ 7:30pm

Where: Pupin 329

Do you know how to file your taxes? Have you started building your credit score? What about your retirement savings? Come learn how to adult your personal finances, backed by data and math. You won’t learn this in school!

Please RSVP.

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Basketball Analytics - Using Machine Learning on Player Tracking Data
Apr
2
to Apr 9

Basketball Analytics - Using Machine Learning on Player Tracking Data

When: Monday, April 2 2018 @ 7:30pm

Where: Fayerweather 313

Join CDSS, Suraj Keshri, and Min-hwan Oh, two PhD students in the Operations Research department, for an exciting talk on advanced analytical techniques in basketball. The talk will discuss ongoing work on exploiting optical tracking data to develop new metrics to better characterize player strengths, including understanding defensive assignment and automatic event detection, and combining trajectory modeling with shot efficiency. Methodologically, this work relies on hidden Markov models, logistic regression, deep neural nets, and unidirectional and bidirectional Long Short Term Memory (LSTM) networks.

Please RSVP.

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CDSS x McKinsey/QuantumBlack
Mar
29
7:30 PM19:30

CDSS x McKinsey/QuantumBlack

For more info.

Come join McKinsey’s New Ventures, Advanced Analytics, and QuantumBlack practices on March 29th, 2018 at 7:30pm ET for a conversation about our work in data analytics and machine learning. We will explain the work these groups do and then talk through a recent project that leveraged machine learning to predict and prevent injuries for a professional sports team. We will also discuss the data analytics and machine learning roles at McKinsey and QuantumBlack. Following the talk, there will be a panel discussion to answer any questions. We look forward to meeting you!

Please arrive at 7:30pm sharp, as we’ll be beginning the presentation then.

Agenda:

7:30 – 8:30pm: Introductions, Analytics Case Presentation, Recruiting Process Overview

8:30 – 9:00pm: Q&A

Presenter Bios:

Muneeb Alam - Muneeb is an Analytics Fellow in McKinsey’s Public Sector Analytics group. He joined McKinsey right out of university, with a BA in astrophysics from Columbia and a Master’s in Analytics from Imperial College London. He’s served clients in corrections, tax, and education.

Daniel First – Daniel is a Data Scientist at QuantumBlack, a subsidiary of McKinsey that specializes in machine learning. After pursuing graduate studies at Columbia’s Data Science Institute as an NSF research fellow, he joined McKinsey initially as a management consultant, before moving over to his current role at QuantumBlack. His work has centered around collaborating with doctors and hospitals to design innovative, data-driven solutions to improve outcomes for patients, by forecasting and preventing medical risks. He has also published on the social and political implications of Artificial Intelligence. He holds a master’s degree in philosophy from the University of Cambridge and an undergraduate degree in neuroscience from Yale University. 

Ishneet Kaur – Ishneet is a Risk Advanced Analytics Fellow with experience in risk identification and stress testing. She interned with Risk Analytics in the Summer of 2016 before joining McKinsey full time in July of 2017. Ishneet holds a Masters in Applied Economics from Cornell University.

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CDSS x IBM: Science for Social Good
Mar
28
7:30 PM19:30

CDSS x IBM: Science for Social Good

For more info.

Join IBM Research on March 28th, 2018 at 7:30pm ET for a conversation about our work using Data Science for Social Good. Members of IBM Research will give an overview of the program, and walk through recent projects that leveraged machine learning to produce social good. Projects include using natural language processing-based methodology to accelerate the work-flow of policy experts at UNDP, Accelerate Science Discovery. Following the talk, there will be a panel discussion to answer any questions. We look forward to meeting you!

Speakers’ Bios:
Kush R. Varshney
Kush R. Varshney was born in Syracuse, NY in 1982. He received the B.S. degree (magna cum laude) in electrical and computer engineering with honors from Cornell University, Ithaca, NY, in 2004. He received the S.M. degree in 2006 and the Ph.D. degree in 2010, both in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge. While at MIT, he was a National Science Foundation Graduate Research Fellow.

Dr. Varshney is a research staff member and manager with IBM Research AI at the Thomas J. Watson Research Center, Yorktown Heights, NY, where he leads the Learning and Decision Making group. He is the founding co-director of the IBM Science for Social Good initiative. He applies data science and predictive analytics to human capital management, healthcare, olfaction, computational creativity, public affairs, international development, and algorithmic fairness, which has led to recognitions such as the 2013 Gerstner Award for Client Excellence for contributions to the WellPoint team and the Extraordinary IBM Research Technical Accomplishment for contributions to workforce innovation and enterprise transformation. He conducts academic research on the theory and methods of statistical signal processing and machine learning. His work has been recognized through best paper awards at the Fusion 2009, SOLI 2013, KDD 2014, and SDM 2015 conferences.

Yaoli Mao
Yaoli Mao is a Ben Wood Research Fellow affiliated with the Institute for Learning Technologies and Ph.D. student in the Cognitive Science in Education program at Teachers College Columbia University. 
She conducts research using both quantitative and qualitative methods in the intersection of cognitive psychology, human-computer interaction and learning science. Yaoli is interested in social and cognitive-affective aspects of learning (engagement, boredom, and gaming etc.), learning strategies and behavior patterns. Her dissertation concerns collective intelligence, exploring knowledge sharing and learning among diverse expertise and human crowds’ intelligence can be properly evaluated, supported and elevated by machine learning and system design.

Jonathan Galsurkar
Jonathan will graduate in May with an MS in Data Science from Columbia University. He graduated summa cum laude in with a bachelor in Computer Science and Mathematics. Before coming to Columbia, he served as adjunct lecturer as well as developer for a health-tech company. Jonathan main areas of interests are machine learning and natural language processing, especially their utilization for social good. DSI students might recognize Jonathan from the 2017 Columbia Data Science Hackathon, in which his team came in first place. As a Science for Social Good Fellow at IBM, Jonathan’s work was focused on sentence/paragraph embedding and semantic searching techniques & applications.

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CDSS: FinTech/AI Panel 2018
Mar
19
7:30 PM19:30

CDSS: FinTech/AI Panel 2018

For more info.

We're excited to present the FinTech Panel 2018! This panel discussion focuses on the disruption of emerging technologies such as Artificial Intelligence and the Internet of Things in the finance industry. The panel will be an hour long, followed by a reception and networking session with the attendees. The panelists for the event are:

Brian Rogers (CEO & Founder, Modgital, Inc.)
-CEO and Founder, ShoShell LLC
-MS in Technology Management (Columbia University)

Michael Wang (CEO & Co-Founder, Sirl.io)
-Adjunct Assistant Professor of Electrical Engineering (Columbia University)
-Director of Internet of Things Practice at Thynk Different
-PhD Electrical Engineering, MS Electrical Engineering (Columbia University)

Steve McClain, a senior software developer at Bloomberg, will be the moderator of the panel.

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Intro to IoT Programming ft. Raspberry Pi
Feb
28
7:30 PM19:30

Intro to IoT Programming ft. Raspberry Pi

For more info.

Get started with your own IoT project and learn how to stream sensor data from a Raspberry Pi to a streaming API for real time visualizations. This first event of our new IoT workshop series will introduce you to the Raspberry Pi computer, programming for IoT projects using Python, and real time data streaming. No prerequisites other than a basic understanding of Python are required!

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Women in Data Science Panel
Feb
21
7:30 PM19:30

Women in Data Science Panel

For more info.

What is it like to be a female data scientist? These unique experiences, both rewarding and challenging, will be shared by a panel of accomplished female data scientists from various companies in different industry sectors, including Capitol One, Audible, NYTimes, and Macys. This is an invaluable opportunity to get a glimpse at the experiences of female leaders in the industry.

The speakers:
Allison Fenichel- Capitol One
Jiun Kim - Audible
Anne Bauer - NYTimes
Iva Horel - Macys

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Applied Data Science and Quantum Computing in Machine Learning
Feb
12
8:00 PM20:00

Applied Data Science and Quantum Computing in Machine Learning

For more info

Applied Data Science and the Emerging Role of Quantum Computing in Machine Learning

Data science has been rapidly growing over the past decade, and its applications have become ubiquitous in our daily lives. As these applications consume more data and need faster response times, new technologies and algorithms are needed to meet the computational demands. Quantum computing is a highly promising emerging technology that could present significant opportunities to accelerate the training of machine learning algorithms and improve data science methods.

This presentation will provide an overview of data science, with a focus on practical applications in industry. The current state of quantum computing technologies will also be explored, including some of the ways that quantum computing can be harnessed to advance machine learning.

ABOUT THE SPEAKERS:

John Kelly, Ph.D.
John Kelly, Director of Analytics at QxBranch, is leading the company’s development of advanced data analytics technologies. Previously, he was the Technical Lead for Corporate Data Analytics at Lockheed Martin. John has experience applying machine learning to a diverse set of domains including healthcare, supply chain optimization, sustainment, and program management. He completed his BS and MS in Electrical Engineering at NC State and his Ph.D. in Electrical and Computer Engineering at Carnegie Mellon University, where his work focused on machine learning and signal processing algorithms for brain-computer interfaces.

About QxBranch
QxBranch (www.qxbranch.com) develops and deploys advanced data analytics models for global companies in finance, insurance, technology, and sports. We have a diverse team of professionals in systems and software engineering, machine learning, quantum computing, and cyber security.
QxBranch is headquartered in Washington, D.C., with offices in London and Australia. For the most up to date career opportunities, please visitwww.qxbranch.com

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Arthena: Tech Talk + Recruiting!
Feb
7
8:00 PM20:00

Arthena: Tech Talk + Recruiting!

For more info.

Arthena is a YC-backed art hedge fund based in NYC. Come hear how we gather millions of records on decades of art auctions and quantitatively analyze, price, and invest in art.

We’re looking for full-time summer interns! Data science interns will build experimental models, expand our data pipeline, build data visualization tools, and contribute to the production machine learning systems we use to invest tens of millions of dollars in art. All internships are paid and based out of our office in SoHo, NYC.

About the speakers:

PAUL WARREN manages the data science team, products, and technical roadmap at Arthena. He is currently co-authoring a data science textbook with a Professor of Data Science in South Korea and has several years of professional data science experience. He studied Computer Science at Stanford, where he grew and managed a 100-person space exploration project group.

BASIL VETAS is a data scientist at Arthena and a graduate student at Columbia's Data Science Institute. He previously worked on the data visualization team at JPMorgan and Qualtrics, with an impact investing fund, and with a number of startups. Basil is originally from Salt Lake City and received his bachelor's degrees from the University of Utah. 

CHIKE UDENZE is a Software Engineering intern at Arthena. He studies software engineering at Rochester Institute of Technology and has previously worked at Releaf (YC Spring '17) and Datto.

*Bring in your résumés!



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The Broadway Room is located on the 2nd floor of Lerner Hall (the big glass building just to the west of Butler Library). Detailed floor plan:http://lernerhall.columbia.edu/files/lerner/floorplans/2e.jpg?width=600&height=800

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Getting Started with Kaggle
Jan
29
7:15 PM19:15

Getting Started with Kaggle

When: Monday January 29 2018 @ 7:15pm - 8:00pm

Where: Lerner 569

For more info

Kaggle is the biggest online Data Science platform which brings together some of the most skilled data scientists out there. It is home to the biggest Machine Learning competitions in the world and is also a treasure trove of resources for both aspiring and seasoned Data Scientists. 

Join us for a workshop that will teach you how to utilize this platform to hone your Data Science skills, attack new data-driven problems, build a portfolio that stands out and get noticed by recruiters!

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ASK CDSS: Course Selection
Nov
29
8:30 PM20:30

ASK CDSS: Course Selection

We know that finals are fast approaching, but just around the corner is an equally daunting task — choosing courses for next semester — especially when so many departments are offering up their takes on a data science curriculum. Let CDSS ease the stress! We'll run through classes for all levels of ability, ranging from the best first-exposure classes to which advanced machine learning class promises to be the most engaging. We'll also leave some time for open Q&A with our undergrad and grad members, who have all taken a different smattering of data science courses over the years.

RSVP on the Facebook event.

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Probability and Statistics for Interviews
Nov
9
8:00 PM20:00

Probability and Statistics for Interviews

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

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Pandas Workshop
Nov
8
9:00 PM21:00

Pandas Workshop

Are you looking to learn the basics of the pandas library for Python for your next data science project or an upcoming interview? Do you want to find out why Pandas is useful for data science and how it can be used most efficiently? Join us for a short session on the basics of dataframes, file I/O, cleaning and viewing data and preparing dataframes for scikit-learn. We will guide you through the basics of pandas using the Kaggle Titanic dataset.

When : Wednesday, November 8 at 9:00pm to 10:00pm

Where : Hamilton 517

For more information and RSVP

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Ask CDSS : Internships
Nov
1
9:00 PM21:00

Ask CDSS : Internships

Getting some experience working on real problems and real datasets is a crucial step towards becoming a data scientist, and the best way to do that while you're in school is a summer internship. But finding the perfect internship is tricky, so let us help you! During this panel, you'll hear from some current CDSS board members about their internship experiences at Facebook, Digital Reasoning, and more- from applying and interviewing to preparing for your first day and landing that return offer. Then we'll open up the floor to you, so come with with questions!

When : Wednesday, October 1 at 9:00pm to 10:00pm

Where : Hamilton 517

For more information and RSVP

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CDSS Town Hall
Sep
13
9:30 PM21:30

CDSS Town Hall

Come on out to the annual CDSS Town Hall meeting! We'll be covering how to join the executive board, events we're planning this semester, and hackathon details. We also want to hear from y'all, so come with questions about anything and everything, as well as ideas for events you want to see this semester.

Dinner will be provided! RSVP to the Facebook event.

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The Anatomy of the NBA Ecosystem
Feb
28
7:00 PM19:00

The Anatomy of the NBA Ecosystem

  • Roone Arledge Cinema, Lerner Hall (map)
  • Google Calendar ICS

For more details and to RSVP, visit the Facebook Event

In a preview of his Sloan Analytics Conference talk, Evan Wasch, SVP of Basketball Strategy & Analytics at the NBA, will break down how the NBA League Office uses data science and analytics to make complex changes to the game and league. A full preview of the talk can be found below:

Behind the scenes, the NBA game is comprised of an intricate web of decision points or “levers,” all designed to maximize the quality of the core basketball product. From in-game aspects like game rules and format to competitive considerations like scheduling, playoff structure, and draft lottery, each lever of the ecosystem is interconnected and even small changes can have significant ripple effects. This presentation will discuss these complex interactions and give a look under the hood on how the NBA uses analytics to make key strategic decisions related to its core product.

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Recommendation Systems and Deep Learning at eBay
Feb
23
7:00 PM19:00

Recommendation Systems and Deep Learning at eBay

RSVP to the Facebook Event!

Recommender systems have become an integral method for discovery of content on the web, such as music, movies, books, search queries, social media content, and consumer products. In the context of e-commerce websites like eBay, they can be a critical part of a user's’ shopping experience, helping the buyers find the best products for them from among the millions that are available. A technique called collaborative filtering is the foundation of modern recommender systems, where behavioral signals such as item clicks and purchases are used to predict whether a user will find an item relevant. In this talk, we give an overview of standard collaborative filtering techniques, describe the challenges of applying collaborative filtering in a semi-structured marketplace such as eBay, and present how we are leveraging deep learning techniques to overcome the distinctive challenges of building recommender systems for eBay listings.

Speaker Bio
Daniel Galron is a research scientist & engineer working at eBay since 2014. He earned a PhD in computer science from NYU in 2012, where he worked on machine learning methods for machine translation.

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Data Science Case Studies with KPMG
Feb
16
7:00 PM19:00

Data Science Case Studies with KPMG

Data Scientists at KPMG work to bring AI, Machine Learning, Advanced Statistical Modeling, and Optimization to our clients. In this talk, we provide examples where we have applied Data Science and Analytics to scheduling a major sports conference, taught computers to read complex financial documents, and provided innovative solutions to our Fortune 500 clients.

Speakers: 
John Lee (Director, Data & Analytics): https://www.linkedin.com/in/john-lee-16156417
Arthur Franke (Manager, Data & Analytics): https://www.linkedin.com/in/arthur-franke-271a1643

Job Links:
http://us-jobs.kpmg.com/careers/SearchResults/data%20scientist
http://us-jobs.kpmg.com/careers/SearchResults/%22big%20data%20software%20engineer%22

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Women in Data Careers Panel
Feb
7
7:30 PM19:30

Women in Data Careers Panel

  • Roone Arledge Cinema in Lerner Hall (map)
  • Google Calendar ICS

Thinking about a career in data science? Curious to know what kinds of jobs you can have as a data scientist in Finance, Healthcare, Retail, Media, and more? Join us for the Women in Data Science Career Panel this Thursday! We have invited an accomplished group of ladies from different areas of data science to share their experiences and give us some tips on job search, work life, and how you too can shape the future of data science.

Non-CUID guests must RSVP to on Eventbrite

More info on the Facebook Event

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Data Science in FinTech
Jan
30
6:00 PM18:00

Data Science in FinTech

  • Davis Auditorium, Schapiro (CEPSR) (map)
  • Google Calendar ICS

Back by popular demand, we've gathered a diverse group of panelists from Betterment, Bloomberg, Kensho, and OnDeck to give their perspectives on the role that data science plays in the FinTech industry. The panelists, as well as representatives from some of companies, will be available for networking at the conclusion of the discussion. To RSVP and learn more about the panelists, visit the Facebook event!

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