NYC Data Science Academy: Data Scientist & Employer Networking Event Jan 2017

NYC Data Science Academy: Data Scientist & Employer Networking Event Jan 2017

Every quarter we invite hiring managers who have openings in Data Science to meet our students at a cocktail party! Gourmet food, wine, music, great people all come together. This time, three alumni from previous cohorts and their managers joined the event. Denis Nguyen (Ameritas Life Insurance Corp), Arda Berkay Koşar (Publicis), Robert Castellano (JP Morgan) attended to share advice, experience, and current openings with the most recent cohort. Companies who joined us include: 7 Park Data, Ameritas Life Insurance Corp, Callida Energy, CitiBank, Education Pioneers, Fino Consulting, Goldman Sachs, IBM Corp, JP Morgan, Memorial Sloan Kettering Cancer Center, Publicis, Research Network on Misdemeanor Justice from CUNY, Tapad, The Michael J Fox Foundation, WorkFusion, IBM Advanced Analytics, NYC Dept of Edu and more. We host the hiring partner/student party every quarter, around middle of Jan, April, July and Oct. If you want to join our hiring partner party or have openings now, reach us at: http://nycdatascience.com/hiring-partners/. We are looking forward to supporting your data science talent pipeline. And we don't charge ANY FEES to place our candidates! We want to build the Data Science community ~ We want to match the best candidates with the right positions. Read more on: https://blog.nycdatascience.com/faculty/jan-24-2017-hiring-partner-event-nyc-data-science-academy/

Katie Critelli, Data Scientist at Deutsche Bank

Katie Critelli, Data Scientist at Deutsche Bank

Katie Critelli had spent years doing research when she was considering an academic career. When she decided that she wanted to have greater flexibility and apply her skills outside academia, she recognized that the path of the data scientist was the one she wanted to pursue. To obtain the necessary skills and the assistance in launching a new career, she enrolled in NYC Data Science Academy. Her role in the newly formed anti-money laundering team at Deutsche Bank lets her apply her skills and creative thinking while learning more on the job. We sat down with Katie to learn more about her background, and why she decided to add Data Science to her resume. Read the full post: https://nycdatascience.com/blog/faculty/alumni-spotlight-katie-critelli-data-scientist-at-deutsche-bank/

Sense Data Scientist at Work

Sense Data Scientist at Work

Watch one of our data scientists trace the electrical signals from an example house and show you how he identifies them as devices, even when signals from multiple devices overlap. For more about Sense, visit: Our website at https://sense.com/ Our blog at http://blog.sense.com/ Our Facebook page at https://www.facebook.com/sense Our twitter at https://twitter.com/TellSense

A Hybrid Recommender with Yelp Challenge Data

A Hybrid Recommender with Yelp Challenge Data

Developed by Chao Shi, Sam O'Mullane, Sean Kickham, Reza Rad and Andrew Rubino This project was completed by students from NYC Data Science Academy's 12-Week Bootcamp. People make decisions on where to eat based on friends’ recommendations. Since they know you, their suggestions matter more than those of strangers. For the capstone project, we built a hybrid Yelp recommendation system that can provide individualized recommendations based on your friend’s reviews on the social network. We built the machine learning models using Spark, and set up a Flask-Kafka-RDS-Databricks pipeline that allows a continuous stream of user requests. During the presentation, we will talk about the development framework and technical implementation of the pipeline. Read on their project posts and code: https://blog.nycdatascience.com/student-works/capstone/yelp-recommender-part-1/ https://blog.nycdatascience.com/student-works/yelp-recommender-part-2/

Making data mean more through storytelling | Ben Wellington | TEDxBroadway

Making data mean more through storytelling | Ben Wellington | TEDxBroadway

Ben Wellington uses data to tell stories. In fact, he draws on some key lessons from fields well outside computer science and data analysis to make his observations about New York City fascinating. Never has a fire hydrant been so interesting as in this talk. Ben Wellington is a computer scientist and data analyst whose blog, I Quant NY, uses New York City open data to tell stories about everything from parking ticket geography to finding the sweet spot in MetroCard pricing. His articles have gone viral and, in some cases, led to policy changes. Wellington teaches a course on NYC open data at the Pratt Institute and is a contributor to Forbes and other publications. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx

Gilad Lotan: "Human vs. Algorithm: Data As the Final Frontier"

Gilad Lotan:  "Human vs. Algorithm: Data As the Final Frontier"

This Ignite NYC took place in conjunction with the O'Reilly Strata Conference on Monday, October 22nd at the Sheraton New York Hotel and Towers in the Metropolitan Ballroom. The theme stemmed from the conference's focus on data science and vizualization, with an focus on the wonder and mysteries that data science is stumbling into. Gilad is the Chief Data Scientist at SocialFlow, a New York startup that analyzes massive amounts of social data. There was a time when Gilad dseigned and built theater sets in Hong Kong Kong. His work has been presented at the Personal Democracy Forum, TED, and SXSW. Twitter: @gilgul Blog: giladlotan.com/blog

Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)

Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)

Ian Wong, Co-Founder of Opendoor, spoke at Data Driven NYC on January 24th, 2017. He explained how Opendoor is utilizing data science to value and purchase homes around the country. Data Driven NYC is a monthly event covering Big Data and data-driven products and startups, hosted by Matt Turck, partner at FirstMark Capital.

Roger Stein: How is managing a data science team different?

Roger Stein: How is managing a data science team different?

MIT Sloan Senior Lecturer and Research Affiliate at the MIT Laboratory for Financial Engineering, Roger M. Stein explains how managing a data science team is different than other teams. A data science team leader may often be involved in the work, but must do it in a strategic way. They should provide oversight and direction, but provide freedom to the team to pursue the research and solve problems in their own way. MIT Sloan Experts Blog: http://wp.me/p2HrZM-1Cy Roger M. Stein Biography: http://mitsloan.mit.edu/faculty/detail.php?in_spseqno=53210

How to Change a City with Data Science by Ben Wellington | DataEngConf NYC '16

How to Change a City with Data Science by Ben Wellington | DataEngConf NYC '16

Discover how Ben Wellington has used data science and his blog "I Quant NY" to make changes in New York City including policy changes with city agencies, subway and taxi pricing, and restaurant scores. In this talk, he dives into the importance of storytelling for data science, and how data science need not include complicated math to demonstrate its power. Learn more about Ben Wellington and his data science talk here: http://www.dataengconf.com/how-to-change-a-city-with-data-science

Kaggle Competion "Walmart Recruiting: Trip Type Classification"

Kaggle Competion "Walmart Recruiting: Trip Type Classification"

Contributed by Brandon Schlenker, Nate Aiken, Joe Eckert, and Daniel Donohue. They enrolled in the NYC Data Science Academy 12-Week Data Science Bootcamp. This was their forth project - Machine Learning project. Kaggle Competion "Walmart Recruiting: Trip Type Classification": http://blog.nycdatascience.com/student-works/walmart-kaggle-trip-type-classification/ Walmart released a data set of purchases for over 1.2 million items (over 600K in each of the training and testing sets) in the hopes that data scientists could predict the type of shopping trip being made. Using logistic regression, random forests, XGBoost and support vector machines will be demonstrated. Bio: Brandon Schlenker, Nate Aiken, Joe Eckert, and Daniel Donohue worked on the Walmart data set. Brandon Schlenker has a B.A. in Math from Northwestern University and most recently finished his Master's in Applied Math from the University of Delaware. Brandon looks forward to a career utilizing machine learning and all things at the intersection of math, statistics, and computer science. Joe Eckert is currently studying with the NYC Data Science Academy to pursue his passion for big data. Joe previously worked for 3 years at JPMorgan's Corporate Bank. He graduated in 2012 with a BA in Financial Economics from the University of Rochester. Joe is a highly motivated, strategic and analytical professional who thrives in high pressure environments. He is an outgoing and charismatic team player with a knack for project management and solving complex problems. Nate Aiken graduated from City College in 2014 with a BS in Biology with a focus in Neuroscience. His experience studying vision and hearing in labs at City and Rockefeller University lead him to the bootcamp. He he enjoys the challenges of working with big data and finding the meaningful relationships within. Daniel Donohue (A.B. Mathematics, M.S. Mathematics) spent the last three years as a Ph.D. student in mathematics studying topics in algebraic geometry, but decided a few short months ago that he needed a change in venue and career. Thankfully, he found the compelling world of data science. From his past experiences, he brings with him a voracious appetite for knowledge and learning, and a keen ability to explain difficult concepts in down-to-earth terms and skills that will serve him well as he looks forward to an exciting and fulfilling career as a data scientist. Learn more about their development framework and code: http://blog.nycdatascience.com/student-works/walmart-kaggle-trip-type-classification/ http://blog.nycdatascience.com/student-works/walmart-and-random-forest/

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