Posted Apr 4, 2017 - Requisition No. 57901
From the biggest banks to the most elite hedge funds, financial institutions need timely, accurate data to capture opportunities and evaluate risk in fast-moving markets. For over 30 years, our clients have relied on our core product, the Bloomberg Terminal, to access the data and analytics they need to make informed investment decisions.
The Derivatives Data Team is building an all- inclusive solution to bring transparency, efficiency, and excellence to this complex market. Our systems face unique problems in processing high frequency and sophisticated financial data. We apply cutting edge technologies like Spark, Cassandra and machine learning to build a data pipeline that produces real time and accurate analytics for our clients. However, that’s just a start. We’re looking for someone to help explore low latency scoring of streaming data, online machine learning, and real time prediction.
As part of this creative team, you will be building a groundbreaking platform which will revolutionize data generation. Our system has to be very low latency to handle the traffic of millions of messages per second. We also have fairly complicated computations, like source confidence evaluation (scoring), online learning for prediction, which need to be carried on in real-time. And of course, like any large scale system, it needs to be scalable enough to handle millions of topic subscriptions.
You will have an opportunity to work with a multitude of technologies: Kafka Streaming, Spark Streaming, Flint, Spark and MLlib.
You will work at the intersection of technology, data science, finance and mathematics. The goal of this platform is analyze, predict, clean and generate best quality derivatives data.