How to Build Our Data Communities Thru Open-Source and Meetups

sam. 26 janvier à 00:30 — informations

Fuseau horaire : Paris (GMT+01:00)

27 E 28th St
New York
New York

Tous les 4 vendredi du mois jusqu'au 1 février 2019

TDP is dedicated to providing a harassment-free experience for everyone, please visit our blog for the full statement of Code of Conduct. Student tickets are available via Eventbrite 【Event】Taiwanese Data Professionals Monthly

【Topic】How to Build Our Data Communities

【Time】01/25 (Friday) 6:30 PM - 8:30 PM

【Location】WeWork Nomad 3rd Floor 27 E 28th St, New York, 10016


Ways to Contribute to Open Source

Soumya will share how important it is to contribute to open source whether it is by analysis or by packages. Open source contributions in the data community are an incredible way to learn and become part of a community. Often making these types of contributions are quite scary and one doesn't know quite where to begin. In this presentation, Soumya will share the approaches she used to start contributing specifically focused in the finance space. She will also demonstrate some of the tools/analysis she built along the way with lessons learned (both good and bad). In addition, she will lay out a path for all data community members to foster more collaboration and contribution. Learnings from Attending Data Events

Three TDP volunteers, Amy, Szu-min, and Yu-ting, will share with us their experiences from attending various data events in NYC. Attending meetups, hackathon, and conferences is one useful way to learn new topics and network. They will share ways to select events to attend and what etiquettes and best practices they have learned. They have been to more than 10 different data communities in New York. 【Speakers】

Soumya Kalra is a quantitative analyst at the New York Federal Reserve where she focusing on developing models and tools as related to stress testing work. She has previously worked at the Securities and Exchange Commission as well as the Department of Treasury. She is currently the lead organizer for R-Ladies New York Board and on the committee for the R in Finance. Amy (I-Peng ) Liu worked in corporate finance and procurement in Asia before switching career in data science. She has a master degree from NYU’s Integrated Marketing department. At IAB, she used excellent SQL and communication skills to support internal clients and improve dashboard performance. She is a key TDP organizer in establishing partnership with other data communities, corporations, and government agency.

Yu-Ting Huang is a data and product person. Before her master degree in business analytics, she worked in material engineering research and led consumer product development team. She's looking for opportunities in forecasting, customer behavior analysis. As a runner, she's interested in personalized training schedule service for runners. Szu-min Yu is a quantitative social scientist with strong machine learning training. She excels in developing compelling narratives from complex data sources whether they are in policing (she now interns with the NYPD), education and career development for women (the topic of her thesis), or employment trends. She has helped building partnership between TDP and RLadies New York communities. 【Schedule】

6:30 - 6:55 networking time (Light refreshment included)

6:55 - 7:00 TDP Introduction

7:00 - 7:20 Talk 1 - Open Source Contribution

7:20 - 7:30 Q&A 1

7:30 - 7:50 Talk 2 - Data Events

7:50 - 8:00 Q&A 2

8:00 - 8:20 Networking

【Moderator】KT Chang


27 E 28th St
New York

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