Applied AI ML Senior Associate

Location: LONDON, LONDON, United Kingdom

Job Family: Predictive Science

About the Role

At JPMorgan Chase, we are at the forefront of leveraging artificial intelligence and machine learning to safeguard our global financial ecosystem. As an Applied AI ML Senior Associate in our Predictive Science team based in London, you will play a pivotal role in designing cutting-edge models that combat fraud and minimize credit risk. This position offers the opportunity to work on high-stakes projects that directly impact millions of customers and billions in transactions, collaborating with a dynamic team of experts in a fast-paced environment. Your contributions will enhance our risk management capabilities, ensuring the integrity and security of JPMorgan Chase's banking operations worldwide. In this role, you will develop and implement advanced AI algorithms to detect sophisticated fraud schemes and predict creditworthiness with greater precision. You will analyze vast datasets from transaction histories, customer behaviors, and market signals, applying techniques like ensemble learning and graph neural networks to uncover hidden patterns. Working closely with cross-functional teams—including risk managers, data engineers, and compliance experts—you will iterate on models to meet evolving regulatory demands and business needs. This is an ideal position for a seasoned professional passionate about using AI to drive innovation in financial services. JPMorgan Chase values innovation, integrity, and inclusion, providing a supportive culture where your expertise can thrive. You will have access to state-of-the-art tools, ongoing training, and opportunities to influence strategic decisions. Join us in London to help shape the future of secure and responsible banking, contributing to a safer financial landscape for our clients and communities.

Key Responsibilities

• Design, develop, and deploy innovative AI and machine learning models to detect and mitigate fraud patterns in real-time transaction monitoring
• Build predictive models for credit risk assessment, incorporating alternative data sources to enhance accuracy and reduce default rates
• Collaborate with data scientists, risk analysts, and business stakeholders to identify high-impact use cases for AI in financial services
• Apply advanced algorithms such as deep learning, ensemble methods, and natural language processing to analyze unstructured financial data
• Conduct model validation, backtesting, and performance monitoring to ensure compliance with internal and regulatory standards
• Integrate ML models into production systems, optimizing for scalability and efficiency in JPMorgan Chase's global banking operations
• Stay abreast of emerging AI trends and technologies, recommending innovations to improve fraud and credit risk frameworks
• Mentor junior team members and contribute to knowledge-sharing sessions within the Predictive Science team
• Analyze large-scale datasets from JPMorgan Chase's transaction and customer systems to uncover insights for risk mitigation
• Partner with engineering teams to automate model pipelines and ensure seamless deployment in cloud-based environments

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field; advanced degree (Master's or PhD) preferred
• 5+ years of experience in applied machine learning, AI model development, or predictive analytics within the financial services industry
• Proven track record of deploying ML models to address fraud detection, credit risk assessment, or similar risk management challenges
• Strong proficiency in Python, R, or Java for data analysis and model implementation
• Experience with big data technologies such as Hadoop, Spark, or cloud platforms like AWS or Azure
• Knowledge of regulatory requirements in financial services, including GDPR, Basel III, and anti-money laundering (AML) standards
• Ability to work collaboratively in cross-functional teams and communicate complex technical concepts to non-technical stakeholders

Preferred Qualifications

• PhD in a quantitative discipline with a focus on machine learning or AI
• Experience in developing AI solutions for fraud prevention or credit scoring at a major financial institution
• Certifications such as AWS Certified Machine Learning or Google Professional Data Engineer
• Prior publications or contributions to open-source ML projects relevant to financial applications
• Familiarity with JPMorgan Chase's internal tools and platforms for model deployment in risk management

Required Skills

• Machine Learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Statistical modeling and hypothesis testing
• Big data processing (Hadoop, Spark, SQL)
• Python or R programming expertise
• Deep learning and neural networks
• Fraud detection algorithms and anomaly detection techniques
• Credit risk modeling (e.g., logistic regression, survival analysis)
• Data visualization tools (e.g., Tableau, Matplotlib)
• Cloud computing platforms (AWS, Azure, GCP)
• Version control and collaboration tools (Git, Jira)
• Problem-solving and analytical thinking
• Communication and stakeholder management
• Regulatory knowledge in financial services
• Agile methodologies and project management
• Ethical AI practices and bias mitigation

Benefits

• Competitive base salary and performance-based annual bonuses
• Comprehensive health, dental, and vision insurance coverage
• Generous 401(k) retirement savings plan with company matching
• Paid time off including vacation, sick leave, and parental leave
• Professional development opportunities through JPMorgan Chase's internal training programs and tuition reimbursement
• Employee stock purchase plan and access to financial wellness resources
• Hybrid work model with flexibility for remote and office-based work in London
• Global mobility programs and international assignment opportunities within JPMorgan Chase

JP Morgan Chase is an equal opportunity employer.