Top Data & Analytics Jobs

As a Vice President in the Quantitative Research team, responsible for providing modelling solutions to the Equity Derivatives business using quant finance and machine learning techniques. Collaborate with traders and Structurers to identify opportunities and develop pricing prototypes. Implement advanced models in trading platforms and leverage machine learning frameworks for problem-solving.

The role involves executing transactions, supporting due diligence, building complex financial models, and drafting presentation materials for M&A activities. Analysts will work closely with clients and senior bankers to contribute to the firm's M&A execution and capital raising capabilities while developing strong functional skills in investment banking.

As a KYC Associate at J.P. Morgan, you will conduct Know-Your-Client activities, ensuring compliance with AML regulations. Key responsibilities include reviewing client documentation, performing due diligence, communicating deficiencies, and collaborating with the Middle Office to complete onboarding processes.

The Applied AI/ML Senior Associate at J.P. Morgan's HR Data & Analytics team will develop data-centric solutions using AI and ML techniques to drive business outcomes. Responsibilities include engaging with stakeholders, developing solutions, and collaborating with teams to achieve the team's vision. Required qualifications include an advanced degree in an analytical field, experience in AI/ML, strong Python coding skills, and previous experience with Spark, Hive, and SQL.

As Vice President in the Machine Learning Scientist - NLP team, responsible for applying advanced ML techniques to tasks like NLP, speech analytics, time series, and recommendation systems. Collaborate with various teams, drive firm-wide initiatives, develop ML models, and contribute to knowledge sharing community. PhD in a quantitative discipline with 3 years of industry experience or MS with 5 years. Strong background in NLP, deep learning, machine learning toolkits, big data, and scalable model training. Experience in designing experiments, intrinsically evaluating model performance, and effective communication.

Research, develop, and implement state-of-the-art machine learning models for NLP, speech recognition, time series predictions, and recommendation systems. Collaborate with various teams to deploy solutions and drive firm-wide initiatives. Independently study, research, and experiment with new innovations in machine learning.

Apply sophisticated machine learning methods in the Time Series and Reinforcement Learning group at JPMorgan Chase. Develop scalable tools for real-world problems in finance and operations, collaborating with various lines of business. Lead projects from conception to deployment of production-level machine learning applications.