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 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 - Minimum Master's Degree with preferred concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline; PhD 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 Machine Learning algorithm development using large scale data - Desire to use modern technologies as a disruptive influence for solving large scale business problems Preferred Qualifications, Skills and Capabilities - Experience in Amazon Web Services - Statistical modeling using machine learning techniques. 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, 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. Note : For your candidature to be considered on this job, you need to apply necessarily on the company's redirected page of this job. Please make sure you apply on the redirected page as well.

Bangalore

JP Morgan Chase - Fraud Risk Data Science Associate 

Job Description for JP Morgan Chase - Fraud Risk Data Science Associate  in JP Morgan Chase in  Bangalore for (2-4) years of experience. Apply Now!