Deep Learning Lead (VP)
Midtown NYC on 7th
A F/T position at a global financial services firm.
Pay Options: F/T Employee.
Contact Claire Volis. call (732)791-4721 / (212)616-4800 ext.590 or email firstname.lastname@example.org with the Job Code CV32265 or Click the Apply Now button ().
Location: Midtown NYC on 7th.
Skills required for the position: MACHINE LEARNING, artificial intelligence, DEEP LEARNING.
Machine Learning is the 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.
- 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
Development/Computing Environment: 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 novel 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.
- 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
- Research publications.
The position offers competitive compensation package.
Job Id: 32265