Full Stack Engineer– CIB- ROAR

JP Morgan Chase - New York, NY (30+ days ago)3.9

About J.P. Morgan Corporate & Investment Bank

J.P. Morgan
J.P. Morgan’s Corporate & Investment Bank is a global leader across banking, markets and investor services. The world’s most important corporations, governments and institutions entrust us with their business in more than 100 countries. With $24 trillion of assets under custody and $423 billion in deposits, the Corporate & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

Who are we looking for?
The ROAR group within J.P. Morgan CIB Data Science is building infrastructure to support a fundamentally new way of approaching data science problems. We are quite unlike a traditional data science group and, rather than assuming human managers are the best organizing principle, experiment with new techniques for achieving Collective Intelligence as it applied to prediction and real-time decision making. Our flagship project is a novel crowd-sourcing platform to be launched mid 2018.

Why join?
We are building a lattice on which, seemingly, every major idea in Machine Learning and Statistics finds a novel spin. This is an engineering and scientific greenfield project requiring careful formulation of statistical, cryptographic and technological problems. It rewards broad peripheral knowledge of applied mathematics, not just recent buzzwords. Tackling our problems will involve significant trial and error, customer feedback and iteration. In exchange for this significant upfront effort we believe we can deliver dramatic cost savings and greater accuracy driving a dramatic lift across dozens if not hundreds of business lines. In addition, you will collaborate with top tier universities helping us pursue civic applications of the new paradigm we are seeking to prove out. You will be joining highly motivated people pursuing this vision, some of whom have founded companies and sold technology to hedge funds, banks and brokerages.

As a full stack engineer or (better termed all-around engineer) you will be improving and expanding all of the technologies that RoarData utilizes.

This is a high impact opportunity as you will be working with quants and researchers, clients and other systems engineers on problems that haven’t yet been solved. Problems will range from being about data storage and access patterns, caching, misbehaving machine learning models, API rate limiting, dealing with eventual consistency, secure cryptography to the big kahuna of being able to being able to predict the future of everything. Don’t worry you’ll have help with all of these problems.

You’ll have exposure to the challenges and feel the rewards of enabling real-time prediction with in a reliable, scalable and secure way. You’re going to hear conversations about gradients (and we’re not talking about things that change colors), probability distributions, sensors, latencies, tensors, the spectral domain, distributed systems, scoring functions and the wisdom of crowds. You’ll be expected to add your own perspective and expertise to these conversations and draw from a wide range of experience to build solutions that will satisfy the goals of RoarData.

You will need to be experienced with these technologies: Linux, Unix, TCP/IP, HTTP/HTTPS/HTTP/2, Websockets, Node.js, C/C++, Python, Amazon or Google Cloud Platforms, SQL and NoSQL Databases.

Additional technologies that would be a major plus are: Golang, asynchronous programming techniques, Machine learning toolkits (TensorFlow, chainer), R, experience with Spark/Presto, Rust.

Other Requirements:
Exceptional coding ability
At least 7 years of relevant professional work experience
A strong academic record with a degree in computer science, computer engineering or another scientific discipline
Experience shipping and supporting production quality code
You’re a critical thinker who really believes in the ability for technology to change the world for the better.
We’re going to be predicting the future but experience in fortune telling, finance or machine learning isn’t necessary.