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JPMorgan Chase10K+ employees

Compliance - Applied AI/ML Lead - Vice President

Jersey City, NJSalary not listedPosted 11 days ago

Immigration summary

Visa sponsorship

Highly likelyHigh confidence

This employer sponsors this kind of work repeatedly, and is still filing this year.

3,104 recent H-1B filings · 37 similar-role filings

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Green card sponsorship

Strong historyHigh confidence

This employer has recently sponsored green cards at scale.

467 recent certified PERM filings · 3 similar-role filings

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Job description

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 Data Scientist Vice President within the Compliance, Conduct Operational Risk Data Analytics organization, you will be responsible for devising and developing Proofs of Concept (POCs) and deployable models using AI/ML techniques, algorithms and other statistical and numerical methods.  You will need to able to extract and work with large volumes of data (both structured and unstructured) from multiple sources, transforming it into an analysis-ready format to develop the data pipeline. Additionally, you are expected to independently formulate methodologies, and quantitative and analytical tasks, from business problems.

Job Responsibilities

Analyze complex/unstructured data to understand the business problem and use case
Analyze business requirements, design, and develop appropriate methodology
Develop deployable, scalable and effective models/ analytical methods as part of technology managed system or as a self-served application of a business user
Work collaboratively and creatively with other data scientists, technology partners, risk professionals, model validation teams, etc.
Prepare technical documentation of quantitative models for internal model risk and governance review

Required qualifications, capabilities, and skills

  • 6+ years of related experience in Python, R or Scala with Bachelor of Science degree in Computer Science, Physical Sciences, Econometrics, Statistics, or other any quantitative discipline.
  • Demonstrable theoretical and application knowledge of Machine Learning methods, and/or Statistical Models
  • Demonstrable hands-on experience and familiarity with any or all of the following packages, algorithms, and/or alternatives, including Graph Learning Packages : (NetworkX, Torch-Geometric, Graphframes,  Graphistry),ML Packages (Pandas, Scikit-Learn, XGBoost, catboost, lightgbm, automl, Optuna, Hyperopt), Visualization Packages (Matplotlib, Seaborn, Geopandas), Algorithm (Ensemble Louvian / Hierarchical Clustering, Label Propagation, Connected Component Analysis, Graph Neural net (Graph Attention Network), Page Rank, Centrality Analysis, Tree based Analysis, Outlier Detection Methods, Zero Shot/ Few Shot learning)
  • Demonstrable experience with LLM prompt engineering and open source LLM fine tuning for a specific domain
  • Demonstrable experience with agentic solution development and insights on how to improve consistency and reliability in agentic behavior
  • Hands-on professional experience in software development especially with analytical & computationally intensive systems, digital transformations leveraging cloud technologies (AWS, GCP, Azure, Databricks etc.)
  • Experience in developing and operationalization of data pipelines 
  • Familiarity and experience of assimilating large amounts of data from multiple databases and utilize them for creating actionable outcome; Adhering to a standardized analysis and project methodology; and Documenting quantitative analysis

Preferred qualifications, capabilities, and skills

  • Post graduate degrees such as Master’s Degree, PhD, etc. is preferred
  • Working knowledge of C/C#/C++ or others is a plus
  • Real life exposure to Agile SDLC, ModelOps and /Or Design Thinking is desirable.
  • Familiarity with Natural Language Processing techniques is a plus
  • Self-starter and strong influencing skills with strong communication skills
  • Experience in financial services industry and/ or, experience with process, controls and governance of a highly regulated environment 

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 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

Sponsorship evidence

Why Openbound reached the conclusions above.

Visa sponsorship evidence

Current posting

Silent on sponsorship

Other openings

165 of 8302 recent openings at this employer state a sponsorship restriction.

Employer H-1B history

3,104
recent certified H-1B filings
896
new-hire petitions
37
filings for similar roles
2,744
so far in FY2026

Filed titles like this role: vice president applied ai ml · vice president ai ml · applied ai ml - vice president · vice president - applied ai ml

More evidence details
  • 37 certified H-1B filings for this same role, 896 new-hire petitions across the employer, and 892 new hires already this year
  • 37 certified H-1B filings for this same role
  • 3,104 recent certified H-1B filings across the employer
  • Still filing this year — 2,744 filings in FY2026
  • 1 USCIS H-1B new-employment approval, counted separately from LCA filings
  • Strong filing activity in NJ
  • 1 further USCIS approval for extensions or transfers
  • 165 other recent postings at this company state a sponsorship restriction
  • The posting says nothing about sponsorship either way

Strong filing activity in NJ.

Green card sponsorship evidence

Employer PERM history

467
recent certified PERM filings
3
filings for similar roles
66
filings in this location
Certified PERM filings by fiscal year
20230
202459
2025711
2026740YTD

Filing history reflects past employer behavior; it isn't a promise for this opening.

All open roles at JPMorgan Chase
How Openbound evaluates sponsorship

Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.

An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 1,128 filing titles were examined for this employer.

What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.