Tech At Bloomberg

Data Science

Improving search and discovery of relevant content, functionality and insights are critical focus areas for Bloomberg’s business.

Our data scientists, AI researchers and quantitative researchers employ machine learning, deep learning, natural language processing, information retrieval and knowledge graph technology across our full suite of products – combining scientific analysis with engineering firepower to solve complex challenges and benefit our customers.

Come see us at NAACL 2022 and SIGIR 2022

NAACL 2022 papers and talks

Combining Humor and Sarcasm for Improving Political Parody Detection
1F: In-Person Poster Session 1 (Monday, July 11 @ 10:45 AM–12:15 PM PDT)
Learning Rich Representation of Keyphrases from Text
Session 9F: Findings In-person Poster Session 1 (Wednesday, July 13 @ 10:45 AM–12:15 PM PDT)
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization
Oral Session 10B: Semantics (Wednesday, July 13 @ 2:15–3:45 PM PDT)

SIGIR 2022 papers and talks

SIGIR Symposium on IR in Practice (SIRIP) 2022 Keynote by Edgar Meij — Search at Bloomberg: Challenges, Opportunities, and Lessons Learned
(Tuesday, July 12 @ 13:40-14:30 CEST)
Analyzing and Simulating User Utterance Reformulation in Conversational Recommender Systems
Conversational IR 2 (Wednesday, July 13 @ 11:00-11:15 CEST)

A collaborative effort

Applications of data science at Bloomberg include search, semantic parsing for question answering, recommendation systems, topic clustering and classification, sentiment analysis, anomaly detection in time series and a variety of other problems. For example, our AI researchers build machine learning models and neural networks to quickly understand and respond to major world events, helping predict when, how and why breaking news will move markets.

Learn more about AI at Bloomberg

Through our internal Machine Learning and Natural Language Processing Guilds, a broad range of engineers share knowledge, tools, code and practices to advance these technologies at Bloomberg and engage with the wider tech community at various conferences. The Guilds also partner with our employee-run Communities to promote diversity in the field of AI, inside and outside Bloomberg.

Engaging with academia

Our AI researchers publish dozens of papers annually and present at leading academic conferences, including AAAI, EMNLP, ICML, KDD, NAACL, NeurIPS and SIGIR, to help advance the field of AI. We also support the research community through meaningful engagement with university faculty, Ph.D. candidates and postdocs, providing grants, fellowship programs, research funding and opportunities to collaborate with Bloomberg data scientists. Access our published research and learn about our Data Science Academic Engagement Programs.

Academic engagement programs

Data for Good Exchange

Explore how Bloomberg’s Data for Good Exchange helps nonprofit organizations and municipalities around the globe improve civic and social outcomes.

Read our latest stories

Our published AI research

Bloomberg contributes back to academia whenever we can by attending and speaking at conferences in ML, NLP, and IR, handing out the Bloomberg Data Science Research Grant, hosting the Bloomberg Data Science Ph.D. Fellows and serving as committee members for conferences.