Risk Management- CCB- Fraud Risk (Data Science) – Associate
Company Name:-
JPMorgan Chase Bank, N.A.
Job Location:-
Bengaluru, Karnataka
Job Summary:-
The Fraud Data Science team uses advanced analytical techniques to mitigate fraud across various payment channels such as Digital Transactions including QuickPay / Quick Deposit, Credit Card, Debit Card and Checks.
The team works closely with business analysts, product owner and operations to find tangible opportunities to prevent fraud, enhance customer experience and provide insights which will allow assessing the risk of portfolio in several dimensions.
The person will need to work on complex problems using Big Data, and Machine Learning.
Develop analytical strategies that can significantly change how fraud is managed and set the path for future
The person will own the project end to end.
He should be able to identify the potential value of data (structured/unstructured) by pulling the data from different sources on the Big data environment, validating and preparing the data for analysis, to be able to use any ML algorithms for the purpose of analysis and deliver actionable insights by doing quick Proof of Concepts, pilots and incremental value outcomes.
Requirements
Partner with various strategy, product, and operational teams to drive multiple analyses on fraud risk across different products.
Will help build a foundation of state-of-the-art technical and scientific capabilities to support a number of ongoing and planned data analytics projects:
Build an in-depth understanding of the problem domain and available data assets
Proactively seeks, finds and recommends opportunities to improve underlying processes.
Use of advanced analytical tools and platforms (including Hadoop) to drive multiple analytical proof of concepts
Research, design, implement, and evaluate machine learning approaches and models
Perform ad-hoc exploratory statistics and data mining tasks on diverse datasets from small scale to “big data”
Investigate data visualization and summarization techniques for conveying key findings
Provides accurate and concise results and presents findings, recommendations and presentations to Management.
Collaborate across cross functional teams to knowledge share and develop broader insights into fraud and customer impacts
Communicate findings and obstacles to stakeholders to help drive the delivery to ma
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