Date: 5th November, Thursday
Time: 11:30am to 1:00pm CST

 

The finance trading lab at the Jindal School of Management is hosting a panel discussion on the topic of Quant & Technology sector. Speakers are professionals and leaders in financial industries and FinTech consulting. They will share with us their insights, career development, and the working environment at their companies followed on by Q&A by our attendees.

About our speakers:

Helen Xing, Ph.D.:  Dr. Xing is a senior quantitative researcher at Cubist Systematic Strategies, the quant arm of Point72 Asset Management. She oversees the PM coverage, data procurement and research for Cubist data team. She started her career at Credit Suisse equity proprietary trading desk where she was a quant trader for 11 years before moving to Cubist. Helen received her Ph.D. in Building Technology, Mechanical Engineering from the Massachusetts Institute of Technology.

Ilana Golbin: Ms. Golbin is the Director at PwC Advisory Emerging Tech Lab, and one of the leads for Artificial Intelligence. Ms. Golbin specializes in applying machine learning and simulation modeling to address client needs across sectors regarding the strategic deployment of new services, operational efficiencies, geospatial analytics, and explainability. Ms. Golbin currently leads PwC’s efforts globally in the development of cutting-edge approaches to build and deploy Responsible AI including bias detection and mitigation, AI governance, AI ethics, robustness & security, and explanation. 

Julia Liang: Ms. Liang is the Vice President of Consumer Technology Solution in Marcus by Goldman Sachs, leading smart contact center solutions that serve Marcus multiple business lines, including Apple Credit Card, consumer lending, and US Deposit, etc. She started her career in AT&T in 1998 as a developer and progressively promoted to architect, Senior Architect, and Principal Architect. Ms. Liang received her MS in Computer Science and Mechanical Engineering from Ohio University.

Stephanie Ma:  Ms. Ma is a risk analyst and team lead at MaxDecisions – a fintech consulting company. She has been working on cutting-edge credit underwriting, marketing, and portfolio management problems combining a wide variety of data for various lending products: personal loans and business loans, installment loans and line of credit, prime and subprime. She received the MS in Business Analytics from the University of Texas at Dallas.

Yahong Cui: Ms. Cui is the head of lending analytics at Citi's Global Consumer Bank. She is responsible for full life cycle strategic analytics in all unsecured lending products, including personal loan, balance transfer, credit line increase, Point of Sales lending, and newly launched innovative Flex programs. Ms. Cui's team drives insights through cutting-edge analytics in segmentation, pricing/offer optimization, Omni-channel strategy, machine learning models, forecasting, and risk management. Yahong received her MBA from Northwestern University and MS from the University of Cincinnati.

Yanping Chen, Ph.D.: Dr. Chen currently works as a quantitative strategist in Goldman Sachs. She previously worked in the data science team at Elevate Credit Service. She is specializing in building machine learning models on large scale financial data. Her modeling experience includes fraud detecting models, risk control models and marketing response models. Dr. Chen will also be our moderator for the event. Dr. Chen received her Ph.D. in applied mathematics from the University of Texas at Dallas.

For valuable consideration, I do hereby authorize The University of Texas at Dallas, and those acting pursuant to its authority to:
 

a)   Record my participation and appearance on videotape, audiotape, film, photograph or any other medium.

b)   Use my name, likeness, voice and biographical material in connection with those recordings.

c)    Exhibit or distribute such recording in whole or in part without restrictions or limitation for any educational or promotional purpose, which The University of Texas at Dallas, and those acting pursuant to its authority, deem appropriate.

d)   Exhibit or distribute any written documentation in whole or in part without restrictions or limitation for any educational or promotional purpose, which The University of Texas at Dallas, and those acting pursuant to its authority, deem appropriate.

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