Applied AI & ML Lead [Multiple Positions Available]

DESCRIPTION:

Duties: Design and develop advanced machine learning (ML) models to detect fraudulent merchant activity and assess payer risk. Engineer graph-based features and embeddings by constructing transaction-level payment graphs across cross-functional teams and applying Graph Neural Networks (GNN) to generate features for fraud detection models. Extract and compute graph connectivity metrics such as PageRank, centrality scores, community detection and label propagation algorithms to identify fraudulent clusters and potential fraud rings within the merchant network. Track and report rule-level model performance metrics, ensuring model interpretability and compliance. Lead model development lifecycle, cross-functional initiatives, and research efforts focused on AI and ML innovation in the trust and safety domain, driving the adoption of scalable, explainable, and high-performing solutions for merchant fraud detection in financial services. Analyze data trends and model outputs to identify potential areas for enhancement and to drive strategic adjustments within the division. Collaborate with machine learning serving teams to deploy production-grade models at real-time pay-in and pay-out transaction checkpoints, ensuring low-latency fraud detection and integration with business-critical systems.

QUALIFICATIONS:

Minimum education and experience required: Master''s degree in Computer Science, Information Technology or related field plus 2 years of experience in the job offered or as Applied Al & ML Lead, Applied Al & ML Scientist/Researcher, Software Engineer, or related occupation. The employer will alternatively accept a Bachelor''s degree in Computer Science, Information Technology or related field plus 5 years of experience in the job offered or as Applied Al & ML Lead, Applied Al & ML Scientist/Researcher, Software Engineer, or related occupation.

Skills Required: This position requires two (2) years of experience with the following: developing and deploying end-to-end supervised and unsupervised ML models, including Decision Trees, XGBoost, LightGBM, and K- means, for fraud detection in the financial services or payments industry; working with high throughput real-time transactional data at scale; using Docker, Kubernetes, and CI/CD pipelines to deploy models such as gradient boosted trees or deep learning architectures; developing graph- based ML solutions for fraud detection with GNNs using GraphSAGE, node2vec, metapath2vec, or Graph Attention Networks; leveraging Pytorch Geometric or NetworkX; creating risk scores using temporal features, rolling aggregates, and longitudinal modeling to support fraud prevention KPIs; building distributed data pipelines for feature engineering and model training using PySpark, Apache Beam, Kafka, and Airflow; building data warehouses that focus on feature freshness and low latency using stacks that leverage BigQuery or Snowflake; using Python, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, and LightGBM for fraud detection model development; implementing model fairness, explainability in SHAP and LIME, and compliance in a regulated financial environment; using model governance in the financial industry, including model risk management reviews, compliance documentation, and responding to audits; working with high-cardinality categorical features in embeddings and statistical smoothing for merchant-level behavior modeling or user device fingerprinting; conducting exploratory data analysis on large-scale, high-dimensional datasets; identifying signals in noisy transaction data, uncovering fraud patterns, and informing feature engineering and modeling decisions; extracting, transforming, and analyzing data from structured financial databases using advanced SQL techniques, including complex joins, subqueries, common table expressions, window functions, and stored procedures; performing scalable data processing using PySpark, BigQuery, Dask, and visualization of distributions; performing time series analysis using matplotlib, seaborn, and Plotly under compute and memory constraints.

Job Location: 3223 Hanover Street, Palo Alto, CA 94304.

Full-Time. Salary: $189,280 - $260,000 per year.

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