DESCRIPTION:
Duties: Develop artificial intelligence and machine learning (AI/ML)-based solutions that drive key credit decisions in the risk management process. Work on strategic, highly visible machine learning projects and interact with business strategy, model governance, data management, and model implementation teams to drive business results. Apply analytical, data science, and machine learning skills to solve complex business problems. Work across teams to design, develop, and implement analytical models. Responsible for these models throughout the model's life cycle, including data cleanup, data analysis, model selection, ongoing performance monitoring, issue resolution, and model retirement. Monitor and validate existing models to support risk strategy and business functions. Liaise with business partners to ensure alignment of the modeling team's Book of Work with the strategic direction of the business. Contribute to the asks and requirements stemming from various regulatory exams. Prepare presentations and reports for both non-technical and technical audiences including senior management, risk strategy and Model Risk Governance and Review (MRGR).
QUALIFICATIONS:
Minimum education and experience required: Master's degree in Finance, Statistics, Computer Science, Mathematics, Engineering or related field of study plus 3 years of experience in the job offered or as Applied AI/ML, Data Scientist, Postdoctoral Researcher, Postdoc Research Associate, or related occupation. The employer will alternatively accept a PhD in Finance, Statistics, Computer Science, Mathematics, Engineering or related field of study plus 1 year of experience in the job offered or as Applied AI/ML, Data Scientist, Postdoctoral Researcher, Postdoc Research Associate, or related occupation. The occupation may be gained through professional work experience, graduate work occupation experience, postdoctoral experience, or internship.
Skills Required: This position requires three (3) years of experience with the following: Applying artificial intelligence (AI) and machine learning (ML) techniques including Logistic Regression, Random Forest, and Gradient Boosting Machine to develop and implement classification and regression models on large-scale datasets; Deploying data analysis, feature-engineering, and model development workflows using Python and SAS. Experience in the skills may be gained through professional work experience, graduate work experience, postdoctoral experience, or internship. This position requires any amount of experience with the following: Utilizing Analytical and modeling methods including logistic regression, gradient boosting machine, multinomial regression, multivariate analysis, discriminant analysis, principal component analysis, factor analysis, and time series analysis; Identifying quantitative relationship embedded within data to predict target variable and inform decision-making; Utilizing Quantitative data management and analytics, including data extraction, cleaning, transformation, and visualization; Designing and developing interactive Excel and PowerPoint reports with advanced functionalities, including LOOKUP, index match, data analysis add-ons, Pivots, and Visual Basic for Applications (VBA); Performing data manipulation, structuring, design flow, and query optimization using programming languages including SQL and Python; Processing large data sets using data containers, multithreading, and multiprocessing in PySpark; Utilizing data science libraries including Pandas, Numpy, Scikit-learn, TensorFlow, Pytorch, Matplotlib and Seaborn and software engineering fundamentals including version control using GitHub and Bitbucket. Experience in the skills may be gained through professional work experience, graduate work experience, postdoctoral experience, or internship.
Job Location: 301 N Walnut St, Wilmington, DE 19801-3935.
Full-Time.
About UsWe offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- Master's in Finance, Statistics, Computer Science, Mathematics, Engineering or related field plus 3 years relevant experience (or PhD plus 1 year).
- 3 years applying AI/ML techniques including logistic regression, random forest, and gradient boosting machine on large-scale datasets.
- Experience deploying data analysis, feature-engineering, and model development workflows using Python and SAS.
- Experience with statistical and analytical methods: multinomial regression, multivariate analysis, discriminant analysis, PCA, factor analysis, time series analysis.
- Quantitative data management skills: extraction, cleaning, transformation, visualization, and identifying predictive relationships.
- Advanced Excel and PowerPoint reporting skills, including LOOKUP, INDEX/MATCH, Pivot Tables, and VBA.
- Programming skills for data manipulation, query optimization, and structuring using SQL and Python.
- Experience processing large datasets using PySpark (data containers, multithreading, multiprocessing).
- Familiarity with data science libraries and frameworks: Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Matplotlib, Seaborn.
- Software engineering fundamentals including version control using GitHub or Bitbucket.
- Ability to prepare presentations and reports for technical and non-technical audiences and support regulatory requests.
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
-
Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
-
Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
-
Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
Gallery
