So, at J.P. Morgan, the interesting thing is that we are a firm that has been around for a long time. But it’s a firm that has a lot of appetite. One thing’s for sure, no two days here ever look the same. I like to start my day in London early. Since we’re a global team, it gives me the chance to review work our New York team did last night and catch up live with my colleagues in India. The Machine Learning Center of Excellence develops and deploys machine learning models across different trading and IT platforms of J.P. Morgan. J.P. Morgan, as a bank, has been incorporating machine learning into a lot of our work flows. So, as a Machine Learning Engineer, this is a great time to work on problems with firmwide impact. We need humans and AI to work together because ultimately, having and learning from what people are doing today in the processes they do and how they operate today provides a great amount of information of how we design systems of the future. External conferences are really important for a number of reasons. One – it allows us to bring in the best of academia and external thought to the organization. The other is that it allows the team to go out to continue to learn. We rely a lot on where we’re going, as well as where we’ve been. So, we come back from a conference knowing where the field is. And how, you know, taking those state of the art methods and applying them to the problems in the bank. The most exciting and novel thing about working with AI Research is getting to publish our work at the most esteemed academic conferences like ICML, AAAI, and NeurIPS. We not only participate, but we also host and sponsor workshops at these conferences. I get to focus on the hot topics in AI and machine learning, such as reinforcement learning, cryptography and explainability. Millions of people use and rely upon our products and services every day. Working here, you have the ability to be on the forefront of changing that interaction. We apply and discover new AI techniques to handle complex problems such as trading, multi-agent market simulations, fraud detection, anti-money laundering and issues related to data. As a technologist I was the most surprised by the wide variety of problems that we have to tackle and that J.P. Morgan is in the unique position to solve thanks to the large amount of data available. We focus on a number of research problems. One of the most exciting ones is ensuring that AI models are explainable, fair and unbiased. In my life span, I don’t expect to see generalized AI become something that’s mainstream. And so for a lot of time we’re expecting to see humans and machine helping each other. Every day is different. Every day we get a new challenging problem. Sometimes there is no known solution for that problem and it is like a new puzzle. Sometimes there is a known solution, but we show how we can do better using state of the art machine learning techniques. There is a lot of belief as we move that AI and machine learning is this one-shot deal. We do it, we are done. We’ll never be done. I work with some of the best and most creative minds in the field and I have ownership over my work which is very rewarding. I’m researching how to apply innovative computer vision and deep learning techniques to understand the complexity of decision making in the financial market and recommend clients for market opportunities What excites me the most about my job here, in New York, is the opportunity to learn from our leaders and external professors. And my favorite part of the day would be brain-storming creative research ideas to solve challenges across all lines of businesses. I’m currently using event logs of Chase customers called ‘Customer journeys’ to find ways to create an even better experience for our clients. We do believe that junior people are the ones, in some sense, that have that vision. That can think big and that they are not kind of like constrained. Our clients are getting younger they want to be interacting in different ways and we need fresh talent to come up and help us with those new ideas and actually implement them in a way that makes sense for the client experience. The advice I would give to a junior executive is to be open-minded. Not to be afraid to learn new things every day. The field is moving very fast. There are many opportunities to learn at J.P. Morgan. Like collaborating with experts in natural language processing, deep learning, time series and reinforcement learning. I’m excited to be part of the transformation to a truly data-driven culture.