Deep Learning Lead (VP)

New York, NY

Post Date: 03/21/2018 Job ID: 10625017 Industry: IT Perm
Description
Brokerage is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm' s employees serve clients worldwide including corporations, governments and individuals from more than 1, 200 offices in 43 countries.
 
As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Brokerage can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.
 
Technology
Technology works as a strategic partner with Brokerage business units and the world' s leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Brokerage' s sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients' businesses— and to our own.
 
 
Brokerage Machine Learning (MSML) is Brokerage' s center of excellence responsible for working with business and IT teams across the firm to solve mission-critical problems. We are a highly motivated and collaborative team consisting of data scientists, machine learning engineers and members from academia. Our team is uniquely positioned to apply advanced AI to revenue generating business cases.
 
Responsibilities
 
- Lead machine learning projects and develop models in collaboration with strats, quants and traders
- Independently work on end-to-end development of models using trading data, market data, alternative data and data from other internal/external data sources
- Bring deep learning insight into econometric modeling 
- Mentor and lead relatively junior members of the team
- Work with stakeholders to refine requirements and communicate progress
- Rapidly prototype and iteratively develop models
- Deploy models to production and monitor performance
- Study recent research and develop original ideas to solve hard problems
- Speak in internal and external forums
 
 
Qualifications
Qualifications
 
Required
 
- Research level understanding of deep learning architectures, their applicability to data and optimal training strategies
- In-depth knowledge of deep learning networks like DNN, CNN, RNN, Auto Encoder, GAN and VAE
- At least 3 years of exclusive experience in deep learning
- Strong command over linear algebra and statistics
- Ability to quickly translate ideas to efficient, elegant code in Python and Tensorflow
- Research oriented mindset with a natural ability to combine traditional techniques and cutting-edge research to develop Client models
- Experience in model training in a GPU environment
- Experience in leading a team of researchers and research engineers
- 5-10 years of machine learning experience
- Excellent communication and presentation skills
- MS in Computer Science, Statistics, Financial Engineering or a related quantitative field. PhD preferred.
 
Desired
 
- Experience in time series analysis and sequential data using ARIMA, Kalman Filters, HMM, RNN etc.
- Reinforcement learning experience in continuous state/action space is highly desirable
- Experience in Bayesian Modeling using MCMC, SeqMC and newer techniques like Variational Bayes

Susan Abrams


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