You will be a part of an expanding new team to transform business practices through data science, automation and quantitative analysis.
Job Summary:
As a Vice President in Quantitative Research, Payments team within the Commercial & Investment Bank, you will be part of an expanding new team supporting 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.
As part of the Commercial and Investment Bank, the Payments business generates around $17bn of revenue annually, holding over $900bn of cash deposits with a global presence in over 160 countries.
Job Responsibilities:
* Reconcile data sources and build data pipelines to form a comprehensive data set fit for modelling 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:
* You have advanced degree (PhD, MSc or equivalent) in Engineering, Mathematics, Physics, Computer Science, etc.
* You demonstrate strong desire to work with data and are comfortable in handling large datasets as well as building efficient data and Machine Learning pipelines
* You demonstrate experience in writing production quality code and familiarity with testing and source control
* You have experience in data analytics using open-source Python packages (pandas/numpy/scikit-learn/tensorflow)
* You demonstrate strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience
* You demonstrate 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, Hackathons or contribution to GitHub
* You demonstrate hands-on experience in solving sequential decision making problems
* You have knowledge/Experience with cloud based infrastructure
* You have experience in building scalable machine learning models
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