Quantitative Research - CIB Payments - Associate

Key Skills

Data pipelines, Effective communication skills, Github, Infrastructure as code, Machine learning techniques, NumPy, Pandas, Python Programming, Quantitative models, Scikit-learn, TensorFlow

Job Description

We are looking for a talented Quant to join the Quantitative Research CIB Payments team in London, as part of the Corporate and Investment Bank, the Payments business generated over $9bn of revenue in 2023, holding over $400bn of cash deposits with a global presence in over 160 countries.

You will be part of a newly formed team that will support the Liquidity and Account Solutions team within Payments, optimizing Net Interest Income and client pricing through the innovative use of data analytics, time series analysis and machine learning. You will help create a globally consistent deposit and pricing toolset used in decision making. 

Job Responsibilities:

• Reconcile data sources and build data pipelines to form a comprehensive data set fit for modeling and visualization
• Build up a scalable data architecture to handle the large volume of transaction data
• Automate existing manual processes and build tools to enable the business to optimize their decision making and deposit management
• Build sequential decision making tools to optimize the net interest income of the business under various liquidity, capital and balance sheet constraints
• Drive projects end-to-end, from brainstorming, prototyping, data processing, data analysis to model development
• Make real-world, commercial recommendations through effective presentations to various stakeholders
• Leverage data visualization to communicate quantitative insights to help business decision-making.

Required qualifications, capabilities, and skills:

• Advanced degree (PhD, MSc or equivalent) in Engineering, Mathematics, Physics, Computer Science, etc.
• A strong desire to work with data and being comfortable in handling large datasets as well as building data pipelines
• Experience in writing production quality code and familiarity with testing and source control
• Data analytics using open-source Python packages (pandas/numpy/scikit-learn/tensorflow)
• Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience
• A strong intellectual curiosity, and an interest in understanding at a deeper level how a bank operates

Preferred qualifications, capabilities, and skills:

• Participation in KDD/Kaggle competition or contribution to GitHub is a plus
• Hands-on experience in solving sequential decision making problems is a plus
• Knowledge/Experience with cloud based infrastructure is a plus
• Experience in building scalable machine learning models is a plus

ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. In accordance with applicable law, we make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as any mental health or physical disability needs.