In the financial world, time is money. And Bloomberg is the fastest provider of market data, financial news and electronic trades in an industry where every second counts. We, the Network Infrastructure team, develop systems that manage the distribution of data across Bloomberg's network for various products. Our key focus when building our high-quality distribution algorithms is the real-time monitoring of changing market conditions, loads on distribution servers and network outages.
 
As a data scientist on our team, you will analyze the efficiency of distribution algorithms and suggest innovative features and enhancements to improve their quality.  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. Right now, we are using Python and Spark to process data from various datastores such as MS-SQL, HDFS, Cassandra, and Splunk. We are also looking to enrich our analytical stack with data visualization tools, predictive tools for building simulations, and powerful exploratory data tools for identifying patterns.
 
We’ll trust you to:

• Partner with various product and engineering teams across the company
• Be self-motivated and thrive in a fast-paced and collaborative environment
• Take full ownership of the full software development life-cycle, including researching infrastructure needs for adopting new technologies

You need to have:

• 3+ years of experience programming in Python/R/SAS/Matlab  or similar technology
• Knowledge of data science and machine learning methodologies
• Background in statistical inference over time-series, unsupervised data in a professional environment
• Knowledge of querying relational databases (MSSQL, Oracle, MySQL) or NoSQL (Cassandra/MongoDB)
• Experience with distributed datastores (Hadoop/S3) or search technologies (Splunk/Solr)
• Self-driven attitude to find new opportunities to increase system performance

 
We’d love to see:


• Knowledge of data visualization tools such as Tableau/QlikView or statistical GoogleCharts/D3.JS
• Familiarity with Spark Batch & Streaming
• Strong communication skills and a collaborative attitude