Overview
In this role you apply advanced ML and NLP to sustainability-related finance challenges at Bloomberg, shaping AI-driven, real-time solutions for investors. You collaborate with domain experts to translate research into production systems and contribute to the sustainability data platform and models. You will work on high-impact problems like real-time controversy detection, emissions estimation, and ML explainability to empower informed decisions. This opportunity blends cutting-edge research with scalable, production-ready systems in a collaborative environment.
Responsibilities
- Collaborate with domain experts to identify and assess sustainability risks
- Own cross-team projects from research to production deployment
- Research and train ML models for sustainability risk assessment
- Design real-time NLP pipelines using large language models
- Develop evaluation frameworks and annotation tooling for continuous improvement
- Stay current with NLP, LLMs, and estimation techniques and translate findings into models
- Represent Bloomberg at conferences and in open-source communities
- Publish product and research findings in documents and venues
Key requirements
- Production ML experience with applications to sustainability or responsible investment
- Hands-on experience with ML problems and Large Language Models
- Ph.D. or relevant MSc in CS, ML, Math, Statistics, Engineering, or related fields and relevant work
- Python proficiency and experience with production ML infrastructure (model serving, data pipelines, evaluation)
- Familiarity with LLM-based systems for information extraction from text
- Solid CS fundamentals and data-oriented problem solving
- Excellent communication and collaboration with engineers and non-engineering stakeholders
- Strong interdisciplinary coordination with sustainable finance analysts and product managers
- Ability to convey research ideas clearly and influence cross-functional teams
- Production ML systems
- Large Language Models
- NLP pipelines
…
