Applied AI ML Engineer-Vice President

Location: New York, NY, United States

Job Family: Predictive Science

About the Role

At JP Morgan Chase, we are at the forefront of innovation in financial services, leveraging cutting-edge AI and machine learning to drive transformative solutions for our clients worldwide. As an Applied AI ML Engineer-Vice President in our Predictive Science team, you will play a pivotal role in applying quantitative, data science, and analytical skills to tackle complex problems in areas like risk management, fraud prevention, and personalized financial advisory. Based in our dynamic New York office, you will contribute to high-impact projects that enhance Chase's leadership in the industry, ensuring our models deliver actionable insights from vast financial datasets while adhering to stringent regulatory standards. In this senior role, you will design, build, and deploy sophisticated ML models using state-of-the-art techniques, collaborating closely with cross-functional teams including traders, risk analysts, and software engineers. Your work will involve end-to-end model development—from data ingestion and feature engineering to validation and production integration—focusing on predictive analytics that inform critical business decisions. You will navigate the unique challenges of the financial sector, such as handling real-time market data and ensuring model interpretability for compliance, all while fostering innovation within JP Morgan's robust technology ecosystem. We seek a passionate leader who thrives in a collaborative environment and is committed to ethical AI practices. This position offers the opportunity to influence strategic initiatives at one of the world's largest financial institutions, with exposure to diverse datasets and advanced tools that push the boundaries of what's possible in predictive science. Join us to shape the future of finance through AI.

Key Responsibilities

• Develop and deploy advanced AI/ML models to address complex challenges in predictive science, such as credit risk modeling and market forecasting at JP Morgan Chase
• Collaborate with data scientists, engineers, and business stakeholders to identify opportunities for AI-driven solutions in financial services
• Apply quantitative and analytical skills to large-scale datasets, ensuring models are robust, scalable, and compliant with industry regulations
• Conduct experiments, evaluate model performance, and iterate on solutions to optimize business outcomes like fraud detection or personalized banking
• Integrate ML models into production systems, leveraging JP Morgan's technology stack for real-time applications
• Stay abreast of emerging AI trends and technologies, advising on their application to enhance Chase's competitive edge in the financial sector
• Mentor junior team members and contribute to the firm's AI/ML best practices and knowledge sharing
• Ensure ethical AI practices, including bias mitigation and explainability in models impacting financial decisions
• Analyze and preprocess financial data from diverse sources to build high-quality predictive models
• Present findings and recommendations to senior leadership to drive strategic initiatives in predictive science

Required Qualifications

• Advanced degree (Master's or PhD) in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field
• 5+ years of experience in applied machine learning, AI, or data science roles within financial services or a related industry
• Proven track record of developing and deploying ML models to solve complex business problems, such as risk assessment or fraud detection
• Strong proficiency in Python, R, or similar programming languages for data analysis and model building
• Experience with big data technologies and cloud platforms like AWS, Azure, or GCP
• Deep understanding of machine learning algorithms, including supervised, unsupervised, and deep learning techniques
• Excellent problem-solving skills and ability to work with cross-functional teams in a fast-paced environment

Preferred Qualifications

• PhD in a quantitative discipline with a focus on AI/ML applications in finance
• Experience working at a major financial institution, such as JP Morgan Chase or similar
• Familiarity with regulatory requirements in financial services, including data privacy and model governance
• Publications or contributions to open-source ML projects relevant to predictive analytics
• Experience with natural language processing (NLP) or time-series forecasting in financial datasets

Required Skills

• Machine Learning Frameworks (TensorFlow, PyTorch, Scikit-learn)
• Python Programming
• Data Analysis and Visualization (Pandas, NumPy, Matplotlib)
• Big Data Tools (Hadoop, Spark)
• Cloud Computing (AWS, Azure)
• Statistical Modeling and Inference
• Deep Learning Techniques
• SQL and Database Management
• Time-Series Analysis
• Natural Language Processing
• Model Deployment and MLOps
• Problem-Solving and Critical Thinking
• Cross-Functional Collaboration
• Communication and Presentation Skills
• Regulatory Knowledge in Finance

Benefits

• Competitive base salary and performance-based annual bonus
• Comprehensive health, dental, and vision insurance plans
• 401(k) retirement savings plan with generous company matching
• Paid time off, including vacation, sick days, and parental leave
• Professional development opportunities, such as tuition reimbursement and access to internal training programs
• Wellness programs including gym memberships and mental health support
• Employee stock purchase plan and financial planning services
• Flexible work arrangements and hybrid office options in New York

JP Morgan Chase is an equal opportunity employer.