Data Science Intern

Quant Modelling Associate

Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

As a Fair Lending Quant Modeling Associate Sr. within the Risk Management and Compliance organization, you are at the center of keeping JPMorgan Chase strong and resilient. You will perform statistical modeling and analyses to detect & mitigate bias in line-of-business models. Your role will involve participating in bias testing-related research projects to support and enhance the bank’s fair lending compliance program.

In this position, you will apply your quantitative skills to help line-of-business developers build fair statistical models that comply with Fair Lending Laws and regulations, including AI/ML models.

JPMorgan Chase and Co. (JPMorgan Chase) is committed to provide fair, equitable, and nondiscriminatory access to credit for both individuals and communities. This commitment is part of our fundamental mission of providing quality financial services to existing and prospective customers in accordance with all applicable laws and serving unique customers. To accomplish this, the Office of Fair Lending (OFL) has a very robust Fair Lending function that oversees firm’s compliance with fair lending laws.

 

Job Responsibilities: 

• Conduct statistical analyses and bias testing to review business models, including traditional models, machine learning / artificial intelligence models (ML/AI) as well as Gen AI based models for fair lending compliance. This role offers a unique opportunity to gain exposure to a wide variety of models across different lines of business, enhancing your expertise and broadening your understanding of diverse modeling approaches.

• Engage with extensive model documentation to thoroughly understand the models you review from a fair lending perspective, allowing you to develop a comprehensive understanding of complex models and their applications.

• Build data-driven algorithms to mitigate potential disparate impact of models by working alongside model developers, business strategy owners & Legal to develop less discriminatory alternative models 

• Prepare presentations & reports to explain statistical results in both non-technical and technical formats to various stakeholders such as senior management, Legal, Model developers, Model Governance etc.

• Perform research & development to keep the fair lending compliance program aligned with industry and regulatory standards 

• Create model documentation; work with Control, Audit and Model Governance teams to ensure adequacy of processes, statistical models and model reviews

• Support the team in maintaining relevant policies & procedures and representing fair lending in regulatory exams, audits and other areas related to internal governance

• Perform other related duties as assigned

 

Required Qualifications, Capabilities, and Skills:

 

• Bachelor degree required in a quantitative field (e.g., Statistics, Economics, Computer Science, Engineering) with 4+ years of relevant work experience, or Graduate degree in a quantitative field with 3+ years of relevant work experience

• Entrepreneurial spirit, strong attention to detail, ability to take the lead on projects, in depth interest in solving complex business problems with data and passion for spreading a culture of change towards data-driven decision making

• Proficiency in Python, shell scripting, cloud computing platforms and tools (e.g., AWS, Spark, Git/Bitbucket, Data Bricks) and database systems (e.g., Snowflake, Hadoop, Teradata, Hive) 

• Experience in developing, implementing and evaluating linear / logistic regression and machine learning / artificial intelligence models

• Experience working or consulting for a bank, a consumer financial product company such as a non-depository mortgage lender or fintech, a banking regulator (e.g., OCC, CFPB) or other similar government regulatory or enforcement agencies with knowledge of how consumer financial products such as mortgage and auto loans are underwritten and priced

• Strong project management, critical thinking and analytical skills; ability to work in a fast-paced environment and manage multiple projects towards completion with focus on quality  

• Excellent communication skills both verbal and written; ability to communicate technical matters in a non-technical way & clearly present complex and sensitive issues

 

Preferred Qualifications, Capabilities, and Skills:

• Experience with bias detection tools or research of fairness
• Experience in LLM prompt engineering and LLM-based model development (e.g., transformers, embeddings, large language models)

JPMorganChase, 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.

Experience Level

Senior Level