Data Scientist Position with Machine Learning Expertise

1 month ago


London, Greater London, United Kingdom Moody's Ratings Full time

We are seeking a Data Scientist to join our Digital Finance team at Moody's Ratings, where you will have the opportunity to develop and deploy machine learning solutions for high-profile data science initiatives.

About the Role

This is a unique chance to leverage your skills in predictive analytics, signal extraction, and explainability to drive business growth and inform decision-making at Moody's. As a Data Scientist, you will work closely with cross-functional teams to design and train models, craft signals from unstructured data, and create actionable insights.

Key Responsibilities
  1. Select and train machine learning models for predictive analytics on diverse datasets.
  2. Build solutions predicting activities and extracting signals from multiple data sources.
  3. Design tools to explain complex predictions in a clear and concise manner.
  4. Collaborate with tech teams to create data ingestion pipelines from various sources.
  5. Work with subject matter experts to incorporate fundamental knowledge into machine learning models.
Requirements

To be successful in this role, you will need:

  • A Master's degree in data science, computer science, statistics, mathematics, or a related quantitative field.
  • Experience in machine learning, with expertise in algorithms and principles.
  • A proven track record of successfully developing and deploying machine learning applications.
  • Strong understanding of tools explaining machine learning predictions.
  • Expertise in Python and SQL programming languages.
  • Proven experience in natural language processing.
  • Excellent communication and presentation skills to convey complex concepts to non-technical stakeholders.
What We Offer

Moodys provides a dynamic and inclusive work environment, competitive salary ($118,000 - $145,000 per year), and opportunities for professional growth and development. Our company values openness, diversity, inclusivity, respect, and a willingness to learn.



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