Data Scientist

Passfort; Brussel Hoofdstad; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Moody's is seeking a Data Scientist to join the Data Estate Analytics team in Brussels, Belgium. You will design, build, and deploy AI-powered workflows that enhance data quality and support business decisions across Moody's Analytics.

We value strong Python, SQL, and ML skills, plus experience in productionizing models and collaborating with engineers. Fluency in English is required; experience with Databricks and cloud platforms is a plus.

Qualifications

• Hands-on experience with AI tools to streamline workflows and deploy AI-powered solutions.
• Proficiency in Python, pandas, scikit-learn, and SQL.
• Solid foundation in statistics, predictive modelling, and ML methods.
• Experience deploying ML models into production environments.
• Ability to analyze large datasets and communicate results to stakeholders.
• Familiarity with Git and collaborative software development.

Responsabilités

• Design, build, and deploy machine learning models and AI-powered workflows that improve data quality, business decision-making, and operational efficiency across Moody's Analytics.
• Develop, test, and deploy machine learning models and AI-powered workflows for defined business use cases.
• Translate business problems into analytical approaches, features, and measurable outcomes.
• Explore and analyse large datasets to surface trends, data quality issues, risks, and opportunities.
• Design and run experiments to validate models, track performance metrics, and measure business impact against defined success criteria.
• Partner with Data Engineers to productionize models through pipelines, monitoring, retraining, and integration into downstream systems.
• Document methodology and present findings and model outcomes clearly to technical and business stakeholders.
• Contribute to team standards through code reviews, reusable components, reproducible experiments, and model documentation.

Connaissances

AI concepts

Python (pandas, scikit-learn)

SQL

Statistics & ML modelling

Production deployment

Data analysis of large datasets

Git version control

English proficiency

Databricks / PySpark

TensorFlow / PyTorch

AWS / cloud platforms

Financial services domain knowledge

Formation

Bachelor's or Master's in Data Science / related field

3+ years ML analytics experience

Outils

Git

Databricks / PySpark

TensorFlow / PyTorch

AWS

Description du poste

Data Scientist

Brussels, Belgium

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

Skills and Competencies

• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use.
• Strong programming skills in Python, including pandas and scikit-learn, and SQL.
• Solid foundation in statistics, predictive modelling, experiment design, and machine learning methods including regression, classification, and clustering.
• Experience developing and deploying analytical or machine learning solutions into production environments.
• Ability to explore and analyse large datasets to identify trends, data quality issues, risks, and opportunities.
• Familiarity with version control using Git and collaborative software development practices.
• Strong problem-solving skills with the ability to communicate technical findings and model outcomes clearly to non-technical stakeholders.
• Professional working proficiency in English.
• Experience with Databricks, PySpark, or other distributed data processing platforms is preferred.
• Experience with modern AI technologies, including large language models, prompt engineering, RAG architectures, agentic systems and AI-assisted development tools such as Claude Code is preferred.
• Familiarity with MLOps practices, including CI/CD, containerization, model monitoring, and AWS cloud platforms is preferred.
• Experience with PyTorch or TensorFlow
• Background in financial services is preferred.

Education

• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• 3+ years of hands‑on experience in machine learning, advanced analytics, or quantitative modelling.

Responsibilities

• Design, build, and deploy machine learning models and AI‑powered workflows that improve data quality, business decision‑making, and operational efficiency across Moody's Analytics.
• Develop, test, and deploy machine learning models and AI‑powered workflows for defined business use cases.
• Translate business problems into analytical approaches, features, and measurable outcomes.
• Explore and analyse large datasets to surface trends, data quality issues, risks, and opportunities.
• Design and run experiments to validate models, track performance metrics, and measure business impact against defined success criteria.
• Partner with Data Engineers to productionize models through pipelines, monitoring, retraining, and integration into downstream systems.
• Document methodology and present findings and model outcomes clearly to technical and business stakeholders.
• Contribute to team standards through code reviews, reusable components, reproducible experiments, and model documentation.

About the Team

Data Estate Analytics works across data science, engineering, business analysis, and product disciplines to turn business questions into analytical models and production‑ready solutions. The team focuses on applying machine learning and AI to data quality, Master Data Management, and company data use cases, with an emphasis on measurable business outcomes and operational efficiency.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law. Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.