News and social media move financial markets. Bloomberg is one of the largest producers of news in the world and we ingest millions of news stories every day from over 70,000 external news feeds and social media such as Twitter. This data keeps our clients informed, and our team's insights help make sense of it for our customers.
Who are we? Bloomberg's Artificial Intelligence (AI) group: researchers and engineers who have a passion for solving complex problems. Our charter: to extract and identify relevant, meaningful, tradable, and actionable information (such as pricings, earnings, recommendations and major events) from data (including news, web, social media, and structured data) in real-time. Since our customers rely on this information to make swift financial decisions, we guarantee precision, accuracy, and latency numbers beyond most academic and industry standards.
We aren't just building customer-facing products, as the infrastructure and algorithms we develop are themselves used across the company. We also publish papers, attend conferences, organize workshops, and contribute back to the larger data science community whenever we can (see https://www.techatbloomberg.com/nlp/ and https://bloomberg.com/company/d4gx/).
Who are you? A research scientist and engineer who wants to work in the areas of machine learning, natural language processing, information extraction, reinforcement learning, graphical models, recommender systems, and/or knowledge graphs. You want to join a close-knit group and make a big impact.
We'll trust you to:
- Work with others in the AI group and the company on production systems and applications
- Publish research findings in leading academic venues and represent Bloomberg at industry conferences
- Write, test and maintain production-quality code
- Design, experiment, and evaluate algorithms, and models
You'll need to have:
- 5+ years of experience in AI, NLP, ML, Optimization, or related fields
- 5+ years of experience programming in C++, Python or Java
- A master’s degree (PhD preferred) with industrial experience
We'd love to see:
- A quantitative background (Probability, Statistics, Linear Algebra, etc.)
- Experience with distributed computational frameworks (YARN, Spark, Hadoop, Kubernetes, Docker)
- 3+ publications in top-tier conferences or journals (such as ACL, AAAI, SIGIR, KDD, EMNLP, ICML, NeurIPS or equivalent)
If this sounds like you, apply!
In addition, do check out our blog, TechAtBloomberg.com/NLP, to learn more about our publications and projects in data science.