Data Scientist III

About this role

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Skills you'll use

What you'll do

• Grade Level (for internal use):

Who can apply

• University degree in Computer Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience).
• 3+ years of hands-on programming experience, primarily in Python, with a strong focus on building, training, and evaluating machine learning and deep learning models.
• Strong experience working with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, Keras, scikit-learn), including designing and implementing neural network architectures.
• Proven experience in computer vision techniques and applications, such as image/video processing, feature extraction, object detection, segmentation, and representation learning.
• Experience developing end-to-end ML workflows, from data preparation and feature engineering through model training, validation, and deployment, with an emphasis on model performance, robustness, and maintainability.
• Working knowledge of data storage and querying technologies (SQL and/or NoSQL) to support analytical and ML workflows.
• Hands-on experience using cloud platforms (such as AWS, Azure, or GCP) for machine learning experimentation, training at scale, and model deployment.
• Familiarity with distributed and accelerated computing concepts relevant to ML workloads (e.g., multi-GPU training, distributed training, or large-scale inference).
• Experience collaborating closely with data engineers and platform teams to integrate models into production pipelines, while maintaining ownership of model logic and performance.
• Exposure to workflow orchestration or experiment management tools (e.g., Airflow, MLflow, or similar) for reproducible ML pipelines is a plus.

Perks & benefits

About S&P Global

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