Applied AI/ML Senior Associate - Payments

Job Description As part of the Commercial & Investment Bank, J.P. Morgan Payments enables organizations of all sizes to execute transactions efficiently and securely, transforming the movement of information, money and assets. We tackle complex challenges at every stage of the payment lifecycle and our industry‑leading solutions facilitate seamless transactions across borders, industries and platforms. Operating in over 160 countries and handling more than 120 currencies, we are the largest processor of USD payments, with a daily transaction volume of $10 trillion. As a Sr. Associate Applied AI/ML Scientist within our Payment Solutions team, you will be instrumental in utilizing artificial intelligence and machine learning technologies to augment our payment solutions and stimulate business expansion. Your role will involve researching, experimenting, developing, and transitioning high‑quality machine learning models, services, and platforms into production to streamline payment processes, bolster fraud detection, and enrich customer experience. You will also be tasked with designing and executing highly scalable and dependable data processing pipelines, conducting analysis, and deriving insights to boost and optimize business outcomes. Working in collaboration with cross‑functional teams, you will identify opportunities for AI/ML applications within the payments ecosystem. Job Responsibilities Actively collaborate with Product, Technology, and other cross‑functional teams to gain a deep understanding of complex business problems and formulate data‑driven solutions to address these challenges in key areas of the payments domain. Design, develop, and deploy machine learning and AI solutions that meet success metrics aligned with business goals, while considering constraints such as model complexity, scalability, and latency. Partner with Risk and Compliance teams to ensure comprehensive model documentation, track performance metrics, and maintain adherence to regulatory compliance standards. Translate model outcomes into business impact metrics and communicate complex concepts to senior management and stakeholders. Required Qualifications, Capabilities, And Skills Master’s degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, Operations Research) with a minimum of 3 years of industry experience. Experience with Shell Scripting, Jupyter notebook, SQL, PySpark, and AWS Cloud Services is required. 2+ years of hands‑on experience with large‑scale data processing on AWS EMR, building robust batched feature stores, and orchestrating SageMaker training, pipelines, and model registry for production ML. Proficient in Python with hands‑on experience in Machine learning and Deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries (NumPy, Scikit‑Learn, Pandas). Essential experience with Jupyter Notebook. 1+ years of extensive experience in Natural Language Processing (NLP) or Large Language Models (LLM), AgenticAI, and 3+ years of extensive experience in other machine learning techniques, including classification and regression algorithms. Strong hands‑on expertise in neural networks and Transformers, including practical experience with Fine‑tuning strategies (full fine‑tuning and parameter‑efficient methods). Experience building data‑driven systems using SQL and distributed processing (Spark, PySpark or equivalent). Solid understanding of algorithms in machine learning, AI, and neural networks, including LLM and Generative AI, and familiarity with state‑of‑the‑art practices and advancements in these domains. Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans. Strong cognitive and communication skills, characterized by clear and articulate expression. Excellent at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes. Preferred Qualifications, Capabilities And Skills Experience in the financial services industry, particularly within investment banking operations. Cloud computing experience: Amazon Web Services, Azure, Docker, Kubernetes, Databricks, Snowflake. Trust & Safety fraud experience in payments, designing and deploying ML models for account takeover, transaction fraud, and promotion abuse. Benefits We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Eligible roles may receive commission‑based pay and/or discretionary incentive compensation. 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. Equal Opportunity Employer 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. #J-18808-Ljbffr JPMorganChase