Position: Machine Learning Research Scientist (Remote)

Location: New York

In the Predictive Analytics AI group, we build data-driven, highly distributed machine learning systems. Our engineers and researchers are responsible for architecting and developing these ML services end-to-end overcoming unique challenges that involve building systems that have high throughput availability, consistency, and low latency. The Predictive Analytics AI Group is the central group in Moody's Analytics comprising of researchers and engineers working together to build data-driven customer-facing products, as well as the necessary infrastructure to support the ML services following the industry leading practices. The group has worked on and built some award-winning AI products like Compliance Catalyst, Adverse Media Monitoring, Corona pulse, Quiqspread, News Edge 2.0, ESG and has participated in various internal automation initiatives. The group also regularly publish and present their work in top-tier academic and industry conferences. We have a flexible work environment and allow remote work depending on one's personal choice.

Broadly, we are looking for colleagues who are passionate about:

• Natural language processing
• Information retrieval
• Information extraction
• Graph Neural Networks
• Recommender systems
• Knowledge graphs
• Explainable AI

We'll trust you to:

• Collaborate with colleagues on production systems and applications
• Design, experiment, and evaluate algorithms as well as models using PyTorch, scikit-learn, Tensorflow, Hugging Face
• Work on POCs and research prototypes
• Provide thought leadership in machine learning
• Represent Moody's Analytics at scientific and industry conferences
• Lead collaboration with colleagues and academia to publish research findings in leading academic venues such as ACL, EMNLP, NAACL-HLT, AAAI, KDD, CIKM, SIGIR, ECIR

You'll need to have:

• Ph.D. in CS, ML, Math, Statistics, Engineering, Quant, or relevant industry experience.
• Publication record in top-tier academic conferences and journals
• Proficiency in modern programming languages such as Python
• Proficiency in leading research projects

Nice to have:

• Experience with MLOPs technologies and workflows
• Experience in working with engineering teams on taking research prototypes to production

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