Job Description
In this role, you will use advanced Machine Learning techniques to mitigate fraud across various payment channels such as Digital Transactions including Quick Pay , Quick Deposit, Credit Card, Debit Card and Checks. You will work closely with business analysts, product owner and operations to find tangible opportunities to prevent fraud, enhance customer experience and provide insights which will allow us to assess the risk of portfolio in several dimensions. If you are intellectually curious and have a passion for driving solutions across organizational boundaries, you may be the perfect fit for our team
Job Responsibilities:
Work on some of the most complex problems imaginable at the intersection Digital, Machine Learning and Fraud. Interact with insanely large and fascinating data to solve real world problems
Develop/ enhance ML models/ tools to create analytical strategies that can significantly change how fraud is managed and set the path for future
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:
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
Communicate findings and obstacles to stakeholders to help deliver the results
Required Qualifications, Skills and Capabilities
Bachelor's degree with concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline; Master’s Degree or PhD on Mathematics, Statistics or similar quantitative subjects preferred
At least 2-4 years of hands-on experience as a data scientist, and advanced proficiency in Python; prior PySpark experience preferred
Fundamental understanding of probability and statistics
Hands-on experience in developing Machine Learning algorithm like Random Forest, XGBoost, Time Series, Unsupervised techniques like Auto-encoder, Isolation Forest etc. using large scale data
Desire to use modern technologies as a disruptive influence for solving large scale business problems
Preferred Qualifications, Skills and Capabilities
Hands on experience on unsupervised learning techniques
Experience in Amazon Web Services
Statistical modeling using machine learning techniques.
ABOUT US
JPMorgan Chase & Co., one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
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, ****** 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.
ABOUT THE TEAM
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
Job Responsibilities:
Work on some of the most complex problems imaginable at the intersection Digital, Machine Learning and Fraud. Interact with insanely large and fascinating data to solve real world problems
Develop/ enhance ML models/ tools to create analytical strategies that can significantly change how fraud is managed and set the path for future
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:
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
Communicate findings and obstacles to stakeholders to help deliver the results
Required Qualifications, Skills and Capabilities
Bachelor's degree with concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline; Master’s Degree or PhD on Mathematics, Statistics or similar quantitative subjects preferred
At least 2-4 years of hands-on experience as a data scientist, and advanced proficiency in Python; prior PySpark experience preferred
Fundamental understanding of probability and statistics
Hands-on experience in developing Machine Learning algorithm like Random Forest, XGBoost, Time Series, Unsupervised techniques like Auto-encoder, Isolation Forest etc. using large scale data
Desire to use modern technologies as a disruptive influence for solving large scale business problems
Preferred Qualifications, Skills and Capabilities
Hands on experience on unsupervised learning techniques
Experience in Amazon Web Services
Statistical modeling using machine learning techniques.
ABOUT US
JPMorgan Chase & Co., one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
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, ****** 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.
ABOUT THE TEAM
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
💡 Quick Summary
Seeking a career-building opportunity? The CCB Risk | Fraud|Data|Science|Associate position is now open for candidates interested in the Bank Jobs sector. This role in Bengaluru offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Bank Jobs is a plus.
