Deep Learning Lead (VP) - job id 32265


Your Way To Work™

Deep Learning Lead (VP)

F/T Employee

Midtown NYC on 7th



How to Apply

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Claire Volis


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(732) 757-2841


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(212) 616-4800 ext-590




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 claire@sans.com 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.


Detailed Info:

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.


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

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.


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


- Research publications.

The position offers competitive compensation package.


Job Id: 32265