Bloomberg Data Scientist - Engineering Client Support in New York, New York

Job Requisition Number: 59225

Our team:

At Bloomberg, everything moves at the speed of light, including our employees. And Bloomberg is the fastest provider of market data, financial news and electronic trades in an industry where every second counts. As the Engineering Technical Operations team, we develop systems that manage data distribution across Bloomberg’s private network, help the Operations department in troubleshooting client issues, & make employees across Bloomberg more efficient.

As a data scientist on our team, you will analyze the data we collect about our network & clients to suggest innovative features & improve the client experience. You will have a unique opportunity to work with product and engineering teams across Bloomberg and devise customized solutions based on their unique needs. You’ll play a key role on the Network Infrastructure team and you will also be part of larger Data Science and Machine Learning community at Bloomberg where you can share your valuable experiences and ideas.

We’ll trust you to:
  • Collaborate with product and engineering teams across the company to translate business problems into data-driven solutions- Write reusable code to transform raw data into actionable insight- Be self-motivated and thrive in a fast-paced environment
You need to have:
  • 3+ years of professional experience programming in Python or R in a Unix environment- Demonstrated success in applying machine learning algorithms and statistical concepts to business problems- Experience working in both NoSQL and relational databases- Experience with distributed data stores (Hadoop/S3)- Expert at correctly processing and manipulating large and complex datasets- Detail oriented and analytical approach to data- Self-driven attitude to find new opportunities to increase system performance
We’d love to see:
  • Professional experience with JavaScript, especially data visualization libraries- Familiarity with Spark- Experience with Docker/Kubernetes, bash scripting, and Splunk