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Year    Hyderabad, Telangana, India

Job Description

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JOB DESCRIPTION
CCOR Fair Lending Quant Modeling Associate Senior
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. Compliance\xe2\x80\x99s Office of Fair Lending 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\xe2\x80\x99s compliance with fair lending laws. Job Summary Office of Fair Lending is seeking a qualified Fair Lending Quant Modeling Associate Senior to perform statistical modeling and analyses to detect & mitigate bias in line-of-business models. This individual will also participate in bias testing-related research projects to support & enhance the bank\xe2\x80\x99s fair lending compliance program. Job Responsibilities As a Fair Lending Quant Modeling Associate Senior in this high-visibility role, you will:
  • Conduct statistical analyses and bias testing to review business models, including both traditional and machine learning / artificial intelligence models (ML/AI),for fair lending compliance
  • 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 8+ years of relevant work experience, or Masters degree in a quantitative field with 6+ 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) and database systems (e.g., Hadoop, Teradata, Hive)
  • Experience in developing, implementing 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
  • Shift timings - 2:30-11:30pm IST
Preferred Qualifications, Capabilities, and Skills
  • Experience in SAS
  • Experience with bias detection tools or research of fairness
ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world\xe2\x80\x99s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.


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\xe2\x80\x99 and employees\xe2\x80\x99 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 professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we\xe2\x80\x99re setting our businesses, clients, customers and employees up for success.

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Job Detail

  • Job Id
    JD3304373
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    Hyderabad, Telangana, India
  • Education
    Not mentioned
  • Experience
    Year