HR at JP Morgan Services
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JP Morgan Chase - Associate - Data Science (6-11 yrs)
Wealth Management - Data Science - Credit Risk - Associate - Mumbai, India
Wealth Management (WM) provides advice, strategies and solutions for all aspects of the financial, asset management and wealth transfer needs of high net worth and ultra-high net worth clients. WM is dedicated to delivering an outstanding client experience by providing unbiased advice and individual solutions.
Credit Risk assesses, permissions and manages credit and counterparty risks on an industry, client, geographic and transaction basis. Credit risk is the risk of loss arising from the default of a client or counterparty. The Credit Risk function identifies, measures, limits, manages and monitors credit risk across our businesses. Credit exposure arises through underwriting, lending and trading activities with and for clients and counterparties, as well as from a range of operating services such as cash management and clearing activities.
This role will be part of the Innovation Team that has been tasked to develop value added risk analytics solutions through the deployment of advanced analytical frameworks and Machine Learning algorithms on top of the firm's big data resources. In particular, the role will focus on leveraging data to enhance the current End-to-End credit risk process across Wealth Management credit.
Responsibilities Include but not limited to:
- Analyze structured/unstructured data from internal and external data sources to drive actionable insights in credit risk.
- Develop and implement machine learning models to deliver risk monitoring capabilities and improve productivity within credit risk processes.
- Perform ad-hoc exploratory analysis and data mining tasks on diverse datasets from small scale to big data.
- Develop data visualization and summarization techniques to convey key findings in dashboards and presentations to senior management.
- Code your solutions (this is a hands-on position requiring strong programming skills on Day-1).
- At least 5 years of professional experience in data science or a related analytical role. Preferably in financial services.
- 2+ years of hands-on experience in Python.
- Bachelor's degree in mathematics, statistics, engineering or equivalent quantitative discipline.
- Practical Data Science knowledge and experience required: Regressions, Clustering, Decision Trees, Ensemble learning like Boosting/Bagging, Neural Networks (Network Analysis experience a plus)
- Thorough understanding of probability and statistics, Bayesian methods, time series analysis
- Knowledge of traditional wholesale credit products will be advantageous.