Are you ready to make a significant impact in the world of AI and machine learning? Join J.P. Morgan's Data Science, Applied AI & ML team, where your expertise will drive innovation in compliance and risk management. We offer unparalleled opportunities for career growth and skill development in AI, machine learning, and data science, all within a collaborative and forward-thinking environment.
As a Data Scientist in the Corporate Oversight & Governance Technology (COGT) team, you will leverage advanced AI/ML techniques, including Large Language Models (LLMs) and Agentic AI, to develop and deploy models for tasks such as anomaly detection, risk assessment, and compliance monitoring. You will work with diverse datasets to enhance our risk management processes and ensure regulatory compliance, contributing to a leading analytics community.
Job Responsibilities
Design, develop, deploy, and manage AI/ML models using advanced techniques, LLMs, and Agentic AI for compliance and risk management solutions.Conduct research on AI techniques to enhance model performance.Collaborate with cross-functional teams to identify requirements, develop solutions, and deploy models in production.Communicate technical concepts effectively to both technical and non-technical stakeholders.Develop and maintain tools and frameworks for model training, evaluation, and optimization.Analyze and interpret data to evaluate model performance and identify areas for improvement.Demonstrate ownership by independently driving projects to success with minimal guidance.Required Qualifications, Capabilities, and Skills
PhD, Master’s, or Bachelor’s degree in a quantitative discipline or an MBA with an undergraduate degree in fields such as Computer Science, Statistics, Economics, Mathematics, etc., from top-tier universities.Minimum of 8+ years of relevant experience in developing AI/ML solutions, with recent exposure to LLMs and Agentic AI, proficiency in coding (e.g., Python, TensorFlow)Solid understanding of advanced statistical methods and machine learning techniques, including transformers and language modeling.Strong ability to understand and interpret data.Advanced problem-solving and exceptional analytical skills.Polished and clear communication with senior management.Ability to deliver high-quality results under tight deadlines and handle large data sets.Required Qualifications, Capabilities, and Skills:
Familiarity with big data platforms (e.g., Hadoop, HDFS, Teradata, AWS Cloud, Hive).Familiarity with data structures and algorithms for effective problem-solving in machine learning workflows.Familiarity with MLOps tools and practices for seamless integration of machine learning models into production.Familiarity with model fine-tuning techniques such as DPO and RLHF.