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 Engineering - Technical Operations 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 business 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:

• Demonstrated success in applying statistical concepts to business problems- Expert at correctly processing and manipulating large and complex datasets
• 3+ years of professional experience programming in Python or R to solve data analytics problems
• Experience with distributed data stores (Hadoop/S3)
• Detail oriented and analytical approach to data
• Self-driven attitude to find new opportunities to increase system performance

We’d love to see:

• Familiarity with Spark
• Experience with Docker/Kubernetes, bash scripting, and Splunk
• Familiarity with Machine Learning algorithms & concepts
• Professional experience with JavaScript, especially data visualization libraries
• Experience working in both NoSQL and relational databases