Machine Learning Risk Modeling

2 months ago

Mumbai, India JPMorgan Chase Bank, N.A. Full time

In this role you will help to develop and manage statistical/ML risk models that support Chase Card Services. If you are intellectually curious and have a passion for driving solutions across organizational boundaries, you may be the perfect fit for our team.
- 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 risk strategy, technology, model governance, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)

**Job responsibilities**
- Own end-to-end risk model development efforts within Core Modeling using advanced statistical/ML techniques like regression, XG Boost, Neural nets, Graph or other traditional modeling/ Machine learning methods.
- Liaison with risk development partners like MRGR, Fair Lending, Legal, Technology and LOB Business Stakeholders.
- Own quality of models developed, assuring accurate and appropriate model development standards, and right implementation of models. Efficiently design and produce models following procedures for model development, validation, and reporting. Provide support for model implementation, performance monitoring and calibration.
- Expected to work on multiple projects with teams in other locations, to ensure high quality model development standards, reviews and re-reviews, model monitoring, enhanced model usage support etc. in compliance with firm's Estimation policies and procedures. Ensure right development and usage of models owned.

**Required qualifications, capabilities, and skills**
- Ph.D. or MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative fields
- 6+ years of experience in developing and managing predictive risk models in financial industry
- At least one year of experience and proficiency in coding (e.g., Python, TensorFlow, Spark, or Scala) and big data technologies (e.g., Hadoop, Teradata, AWS cloud, Hive)
- Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network - CNN and RNN, Clustering, Recommendation) as well as design and tuning
- Polished and clear communication

**Preferred qualifications, capabilities, and skills**
- Demonstrated experience in designing, building, and deploying production quality machine learning models such as XGBoost, GBM, etc. Experience in interpreting deep learning models is a plus
- Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired
- Strong ownership and execution; proven experience in implementing models in production
- Good presentation skills both written and oral are required for this role. Ability to multi-task and present quantitative information succinctly is required.

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.

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