J.P. Morgan Payments is looking to utilize artificial intelligence and machine learning technologies to augment its services, stimulate business expansion, and tackle complex challenges in the payment lifecycle.
Requirements
- Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services is required.
- Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas).
- Experience with Jupyter Notebook/Lab is essential.
- 6+ years of extensive experience working in ML domains like Fraud prevention, Trust and Safety, Ads, Recommender systems with hands on experience working with both numerical and textual or image data.
- Solid Understanding and past experience applying ML models including decision trees, random forests, neural networks, graph models and Large Language Models (LLMs).
- Proficient in both basic and advanced exploratory data analysis (EDA), with an understanding of the limitations and implications of different methodologies.
- Cloud computing: Amazon Web Service, Azure, Docker, Kubernetes, DataBricks, Snowflakes.
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.
- Designing and executing highly scalable and dependable data processing pipelines, conducting analysis, and deriving insights to boost and optimize business outcomes.
- Collaborating with cross-functional teams to pinpoint opportunities for AI/ML applications within the payments ecosystem.
- Researching, experimenting, developing, and implementing high-quality machine learning models, services, and platforms to streamline payment processes, bolster fraud detection, and enrich customer experience.
Other
- Master’s degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research) with a minimum of 6 years of industry experience.
- Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans.
- You possess strong cognitive and communication skills, characterized by clear and articulate expression.
- You excel at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes.
- Bring an AI-ML first thinking to our Fraud and Risk solutions and thus achieving Operational Excellence across the Organization.
