The goal of J.P. Morgan AI Research is to explore and advance cutting-edge research in AI, including ML as well as related fields like Cryptography, to develop and discover principles of impact to J.P. Morgan’s clients and businesses.

Delivering excellence at the intersection of data science, research and industry expertise, our AI, Machine Learning and Data Analytics teams go beyond where any bank has gone before. We ask the questions and find the answers to create solutions and technology that help to solve the world's most pressing problems, improving and protecting our customer and client experiences every day. Whether you’re working with artificial intelligence, big data, machine learning or robotics, our entrepreneurial team environment challenges you to push the limits of your expertise in the pursuit of impactful and commercial real-world applications.

As a Data Scientist Intern on the AI Research team, you will engage in statistical analysis and software development for the benefit of internal and external clients. You will design and build big data solutions using modern data science tools and workflows while collaborating with both the product development and technical teams to provide technical designs as well data science expertise for our clients.

Job responsibilities

• Lead technical discussions with customers, vendor partners, and colleagues from various departments such as Technology, Quant Research & Product Development
• Effectively communicate advanced statistical and technical concepts to various audiences
• Be an expert demonstrating advanced data science workflows and technologies for financial markets use cases
• Confidently make recommendations regarding data science and big data workflows to customers and partners
• Develop examples, applications and tools including tutorials, reference implementations, presentations that will be used by data science practitioners as well as decision makers
• Provide feedback to product, quant, and engineering teams to help shape product development and strategy
• Balance multiple tasks, client engagements and continuous learning to keep up with academic trends

Required qualifications, capabilities and skills

• Understanding of a wide range of statistical models (e.g. regression, tree-based methods, artificial neural networks)
• Good programming skills in at least one of the commonly used languages for data analysis (e.g., Python, R, MATLAB, Scala).
• Experience with applying data science/quantitative modeling to real world, financial use cases
• Knowledge of open source data analysis tools and machine learning libraries
• Experience in creating technical documentation and presentations and the ability to present to a technical and non-technical audience
• Comfortable in a fast-moving environment with often loosely defined tasks where interaction with senior management is required
• Passion and motivation for constant learning

Preferred qualifications, capabilities and skills

• Currently pursuing a Master’s degree or PHD in a quantitative discipline
• Knowledge of cloud data science and machine learning services
• Experience with tools for large scale and distributed data analysis (e.g., Spark)