Lead Deep Learning Researcher 3111037

  • Company:
    Search Canada Jobs
  • Location:
  • Salary:
    negotiable / monthly
  • Job type:
    Full-Time
  • Posted:
    1 month ago
  • Category:
    Customer Service

Company Profile Morgan Stanley is a global financial services firm and a market leader in investment banking, securities, investment management and wealth management services. With offices in more than 43 countries, the people of Morgan Stanley are dedicated to providing our clients the finest thinking, products and services to help them achieve even the most challenging goals. As a market leader, the talent and passion of our people is critical to our success. We embrace integrity, excellence, team work and giving back. Technology The Technology division partners with our business units and leading technology companies to redefine how we do business in ever more global and dynamic financial markets. Our sizeable investment in technology results in leading-edge tools, software, and systems. Our insights, applications, and infrastructure give a competitive edge to clients’ businesses—and to our own. Institutional Securities Technology (IST) develops and oversees the overall technology strategy and bespoke technology solutions to drive and enable the Institutional businesses and enterprise-wide functions. Our clients include Fixed Income, Equities, Commodities, Investment Banking, Research and Global Capital Markets as well as Operations, HR and Corporate Services. Position Description: Morgan Stanley Machine Learning (MSML) is Morgan Stanley’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 Company Profile Morgan Stanley is a global financial services firm and a market leader in investment banking, securities, investment management and wealth management services. With offices in more than 43 countries, the people of Morgan Stanley are dedicated to providing our clients the finest thinking, products and services to help them achieve even the most challenging goals. As a market leader, the talent and passion of our people is critical to our success. We embrace integrity, excellence, team work and giving back. Technology The Technology division partners with our business units and leading technology companies to redefine how we do business in ever more global and dynamic financial markets. Our sizeable investment in technology results in leading-edge tools, software, and systems. Our insights, applications, and infrastructure give a competitive edge to clients’ businesses—and to our own. Institutional Securities Technology (IST) develops and oversees the overall technology strategy and bespoke technology solutions to drive and enable the Institutional businesses and enterprise-wide functions. Our clients include Fixed Income, Equities, Commodities, Investment Banking, Research and Global Capital Markets as well as Operations, HR and Corporate Services. Position Description: Morgan Stanley Machine Learning (MSML) is Morgan Stanley’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 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 – PhD in Computer Science or Machine Learning 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 Knowledge of French and Englishis required. IND1 Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. 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 – PhD in Computer Science or Machine Learning 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 Knowledge of French and Englishis required. IND1 Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential.