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Data Scientist

Brussels, Brussels Capital

Live, first seen by us 17 days ago
Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Design, build and deploy machine learning models and AI-powered workflows

  • Explore large datasets to surface trends, data quality issues, and risks

  • Design and run experiments to validate models and measure business impact

  • Partner with Data Engineers to productionize models and monitor them

  • Document methodology and present model outcomes to technical and business audiences

From the employer’s posting
Design, build, and deploy machine learning models and AI-powered workflows that improve data quality
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
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.

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.
Education & alternatives
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.
Apply at Moody's

Posting record

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Status in our records
Live
First seen by us
Oct 28, 202617 days ago
Recorded sightings
25
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 17

Similar jobs usually come down between day 8 and day 60.

At Moody's, jobs usually come down by about day 15.

From 11,783 similar postings that came down, and 78 of Moody's’s. Coming down is not always a hire.

Moody's is hiring

54 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
  • 11% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Databricks
  • pandas
  • PySpark
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
- 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 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
- 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.

Your next step

Complete your application on careers.moodys.com. The employer’s form will show what is required.

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About Moody's

People
About 5,300 in 2025, up 10% from the year before.Annual report (SEC Form 10-K)
Company
Listed as MCO.

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,403, the most 2,949, and the latest week had 2,098.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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.

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Brussels, Brussels Capital

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