. Morgan’s Payments network is the largest in the world, processing $9.8 trillion daily in more than 120 currencies and 160 countries in 2023. The business offers a complete suite of products and services (Payments, Liquidity, Trade and Finance) with real-time insights and expert client advice, enhancing our ability to manage cost, complexity, and risk.
As a Machine Learning expert for Payments Operations in our industry-leading Applied AI and ML team, youwill be engaged to design and implement high quality solutions for the complex business problems we face at JPMorgan. We have rewarding technical challenges, large data sets and a tremendous opportunity for innovative and exciting machine learning projects.
You will be called upon to draw from your research and work experience to help us implement intelligent and practical algorithms. The ideal candidate will have a deep understanding of the techniques, models and best in class practices in machine learning and will have insight into what works best in real-world situations. You will be at the center of prescribing, designing, and building mission-critical solutions.
We're looking for humble, enthusiastic, bright, and personable people with strong communication skills and a deep knowledge of machine learning. We need a proven track record in innovation with strong potential for growth into a leadership position. A background in finance is not a must-have. If you get as excited about machine learning theory as you get about Python and software development, we’d love to speak with you.
Job Responsibilities
Learning about and understanding our supported businesses in order to drive practical and successful solutions Choosing, extending and innovating ML strategies for various banking problems Documenting and explaining the rationale and design considerations behind the selection of an ML approach Analyzing and evaluating the ongoing performance of developed models to comply with industry regulation Collaborating with engineering teams to deploy Machine Learning services that can be integrated with strategic platforms Communicating AI capabilities and results to both technical and non-technical audiences
Required Technical Qualifications and Experience
Masters degree or PhD in a quantitative or computational discipline, with demonstrated expertise in a variety of classical ML techniques, including natural language processing, clustering, optimization, feature selection, classification Considerable commercial experience in line with a capable individual contributor Strong Python development and debugging skills Ability to work both individually and in collaboration with others, and to mentor more junior team members Ability to work with non-specialists in a partnership model, conveying information clearly and create a sense of trust with stakeholders
Preferred qualifications, capabilities and skills
Experience with deep learning frameworks (pytorch, tensorflow) Experience with ML development principles (. train-test performance, bias-variance tradeoff) and common techniques (decision trees, clustering, neural networks) Experience with natural language processing frameworks (huggingface, spacy, nltk, embeddings, language models) Working understanding of MLOps concepts (CI/CD, versioning, reproducibility, development best practices)
