JPMorgan Chase CIB QR - Quantitative Research - Cross-Asset Client Analytics & Digital Intelligence - Associate/VP in New York, New York
Who are we?
We are a team of data scientists within the Corporate & Investment Bank, focused on using advanced machine learning techniques to find new growth opportunities, drive efficiencies in our businesses and better serve our clients and markets. We work closely with the sales & trading businesses to identify potential opportunities to drive transformation through advanced analytics and enrich the sales process as well as client experience on digital platforms. Given the cross-asset nature of our role, we work with a wide range of proprietary financial datasets – both structured and unstructured, internal as well as external/alternative datasets. Our mission is to leverage these diverse datasets to build impactful, innovative machine learning solutions that drive client engagement and revenue.
What would you be doing?
As an Associate you would:
Research, implement and test machine learning models to solve problems
Survey literature to understand how existing techniques could be used/adapted; develop new techniques as needed
Propose different modeling solutions and systematically test them; develop ongoing model monitoring processes
Develop modular, scalable code that can be leveraged across the team and where applicable by the broader ML community at JPMorgan
Communicate results to stakeholders and the broader team through presentations and technical papers
Work with product and technology teams to deliver solutions to production
As a VP you would (in addition to the above):
Proactively drive exploratory discussions with business stakeholders for new data science products
Provide thought leadership around new techniques being published in the external ML research community
Drive best practices for rigorous, reproducible research and reusable code
Manage communication with stakeholders
Manage and own data science products through the lifecycle of conception, implementation, testing and delivery
Coach and mentor junior members on the team
Opportunity to innovate and drive measurable commercial value in an industry that is being transformed by machine learning
Collaborate with a highly skilled and passionate team with diverse experiences (technology, finance, academia) and specializations (NLP, Bayesian statistics)
Stay sharp and keep learning! Attend and publish at academic and industry conferences; Participate and learn from our internal talk series and study groups where data scientists across teams share their work/personal projects/interesting papers
What do you need?
Masters or Ph.D. in Computer Science, Statistics, Operations Research or other quantitative fields
Experience in research, development and evaluation of machine learning models to solve problems
Proficiency in Python; technical skills in data preparation for analysis
Experience with deep learning frameworks such as Tensorflow/Torch and using open source packages for ML/NLP
Ability to write clean, scalable, production-ready code
Ability to communicate technical concepts and results to a non-technical audience and a keen interest in understanding business requirements
Expertise in Natural Language Processing, Deep Learning, Reinforcement Learning, Recommender systems or financial markets is a plus
About J.P. Morgan Corporate & Investment Bank
J.P. Morgan is a premier corporate and investment bank with a full suite of global financial services and capabilities. The world’s most important corporations, governments, financial institutions, pensions, sovereign wealth organizations, states and municipalities entrust us with their business in more than 100 countries. We offer strategic advice, lend money, raise capital, help manage risk, extend liquidity, buy and sell securities and provide many other banking services in markets around the world.
JPMorgan Chase is an equal opportunity and affirmative action employer Disability/Veteran.