Data Science Intern

Stack

Responsibilities

• ▹Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• ▹Apply AI/ML tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets
• ▹Build reusable QA tools in Python or R that can be automated and scaled across internal pipelines
• ▹Work with research teams, the development team, and other stakeholders to make the best use of asset location data
• ▹Contribute to model documentation, reproducibility, and version control of data science assets

Requirements

• ▹Proficiency in Python (preferred) or R, including pandas, numpy, scipy, scikit-learn, xgboost, lightgbm
• ▹Familiarity with SQL
• ▹Understanding of data quality dimensions: accuracy, completeness, consistency, uniqueness, timeliness
• ▹Knowledge of exploratory data analysis (EDA) techniques to assess dataset health

Nice to have

• ▹Exposure to MLOps or reproducible science tools (DVC, MLflow, Jupyter Notebooks); geospatial libraries are a plus
• ▹Experience with automated testing of data pipelines, validation schemas, and data version control
• ▹Experience with cloud computing environments (Google Cloud, Azure, or AWS)

Soft skills

What we offer

• ▹Transparent compensation schemes and comprehensive employee benefits
• ▹Flexible working arrangements, advanced technology, and collaborative workspaces
• ▹Global Orientation program, Learning@MSCI platform, LinkedIn Learning Pro
• ▹Multi-directional career paths, internal mobility and expanded roles

About the company

MSCI is a leading provider of decision-support tools and services for the global investment community, with over 50 years of expertise in research, data, and technology. Its Climate Risk Center builds geospatial datasets and models that help investors assess physical and biodiversity risks.