JP Morgan - Associate/Vice President - ML Model Governance/ML Model Standardization - CIB

ML Model Governance / ML Model Standardization : Associated / VP

- J.P. Morgan's Corporate & Investment Bank is a global leader across banking, markets, securities services and wholesale payments. The world's most important corporations, governments and institutions entrust us with their business in more than 100 countries. The Corporate & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

- Data Analytics at J.P. Morgan Corporate Investment Bank combines cutting edge machine learning techniques with the company's unique data assets to optimize all the business decisions we make. In this role, you will be part of our industry-leading data analytics team, and advance the state-of-the-art in financial applications ranging from generating business intelligence to predictive models and automated decision making. The role will be in the firm's Applied AI and Machine Learning organization.

- This position is for a talented quant profile with machine learning experience. The candidate will become a part of the team responsible for standardization of the Machine Learning models used within the CIB. The role involves partnering with model development teams as well as the model validation team globally to test, enhance and develop such models, and to create a standardized testing framework to facilitate a timely and robust review.

The team mandate includes :

- Participating in cutting edge research and applying machine learning and data science methodologies to financial markets and related operations

- Analyzing and developing mathematical models for systematic quantitative trading strategies, for example Electronic Trading Algorithms, Index Arbitrage as well as models in operational space for automation of use cases

- Provide feedback and collaborate with users and developers to ensure optimal development of ML models

- Develop and maintain a list of tests to validate various common techniques used to build Machine learning models

- Guiding models through the review process and enhancing and improving them as required

- Evaluate new ML vendor tools for usefulness, effectiveness and ease of deployment in CIB

Qualifications :

- Master's, PhD, or equivalent degree program in mathematics, sciences, statistics, econometrics, engineering, financial engineering, computer science, or other quantitative fields

- Mastered advanced mathematics and statistics (i.e., probability theory, time series, econometrics, optimization), with core expertise in statistics and machine learning theory, techniques, and tools

- Prior knowledge and experience of NLP will be a plus

- Exceptional analytical, quantitative, and problem-solving skills

- Programming experience with one or more of Python, R, MATLAB, TensorFlow, optionally C++

- Strong written and oral communication and interpersonal skills

- Ability to ask incisive questions, converge on critical matters, assess materiality and escalate issues

- J.P. Morgan's group provides a rewarding work environment with excellent opportunities for new hires to develop their abilities and their careers through the breadth and diversity of the activities it covers.