Fraud Modeling - Machine Learning Associate

Aumni

Aumni

Software Engineering, Accounting & Finance
Mumbai, Maharashtra, India
Posted on Sep 23, 2024

Job Description

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.

As a Fraud Modeling - Machine Learning Associate within our Consumer and Community Banking Risk Modeling team, you will be responsible for the development and implementation of machine learning models, statistical models, segmentations, and strategies. Successful candidate will utilize big data and distributed computing platforms, applying them to risk management for our consumer and small business portfolio. In this role, Successful candidate will contribute to long-term profitable growth through strong business acumen, work collaboratively within a team environment, and effectively communicate results to senior management. Our Firmwide Risk Function is focused on cultivating a stronger, unified culture that embraces a sense of personal accountability for developing the highest corporate standards in governance and controls across the firm. Business priorities are built around the need to strengthen and guard the firm from the many risks we face, financial rigor, risk discipline, fostering a transparent culture and doing the right thing in every situation. We are equally focused on nurturing talent, respecting the diverse experiences that our team of Risk professionals bring and embracing an inclusive environment. Chase Consumer & Community Banking serves consumers and small businesses with a broad range of financial services, including personal banking, small business banking and lending, mortgages, credit cards, payments, auto finance and investment advice. Consumer & Community Banking Risk Management partners with each CCB sub-line of business to identify, assess, prioritize and remediate risk. Types of risk that occur in consumer businesses include fraud, reputation, operational, credit, market and regulatory, among others.

Job responsibilities

  • Utilize cutting-edge approaches to design and develop sophisticated machine learning models to drive impactful decisions for the business
  • Leverage big data/distributed computing/cloud computing platforms to optimize and accelerate model development processes
  • Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production
  • Collaborate with various partners in marketing, risk, technology, model governance, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)

Required qualifications, capabilities, and skills

  • Ph.D. or MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative fields
  • Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network – CNN, RNN and Transformer, Clustering, Recommendation) as well as design and tuning procedures
  • Polished and clear communication

Preferred qualifications, capabilities, and skills

  • Minimum 6 years of experience in developing and managing predictive risk models in financial industry
  • Demonstrated experience in designing, building, and deploying production quality machine learning and deep learning models. Experience in interpreting deep learning models is a plus
  • Minimum 4 years of experience and proficiency in coding (Python, Tensorflow or PyTorch, PySpark, SQL), familiarity with cloud services (AWS Sagemaker, Amazon EMR)
  • Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is a plus
  • Strong ownership and execution, proven experience in implementing models in production

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, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

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.