About The Role

As a member of the Data Transformation team, you will play a pivotal role in building and deploying machine learning-powered products and capabilities. Your work will focus on natural language understanding, data extraction, information retrieval, and data sourcing solutions for S&P Global Market Intelligence and its clients. You will lead the development of production-ready AI products and pipelines, fostering a culture of thoughtful risk-taking and self-initiative within a global team environment.

The Impact

The Data Transformation team has a proven track record of delivering breakthrough products and significant business value. In this role, you will be instrumental in developing the next generation of innovative products and enhancing existing ones to solve high-impact business challenges.

What's In It For You

• Contribute to building solutions at an enterprise scale within a global organization.
• Collaborate with a highly skilled and technically proficient team.
• Tackle complex, high-impact problems that drive significant business value.

Key Responsibilities

• Design, develop, and deploy ML-powered products and pipelines.
• Manage all phases of the data science project lifecycle:
• Identify suitable data science project opportunities.
• Collaborate with business leaders, domain experts, and end-users to understand business needs, data, and gather requirements.
• Evaluate and interpret results, presenting findings to business leaders.
• Perform exploratory data analysis, proof-of-concept modeling, model benchmarking, and set up model validation experiments.
• Train large models for both experimentation and production environments.
• Develop production-ready pipelines for enterprise-scale projects.
• Conduct code reviews and optimize code for projects and the team.
• Lead deployment and model scaling strategies.
• Manage stakeholders and represent the team to leadership.
• Mentor team members and lead by example, including facilitating project scrums.

What We're Looking For

• Minimum of 2 years of professional experience in Data Science.
• Expertise in Python, including libraries like Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, and HuggingFace.
• Experience with State-of-the-Art (SOTA) NLP models and expertise in text matching techniques (e.g., sentence transformers, word embeddings, similarity measures).
• Expertise in probabilistic machine learning models for classification, regression, and clustering.
• Strong experience in feature engineering, data preprocessing, and building ML models for large datasets.
• Exposure to Information Retrieval, Web scraping, and large-scale data extraction.
• Proficiency in Object-Oriented Programming (OOP) design patterns, Test-Driven Development (TDD), and enterprise system design.
• Solid SQL skills (any variant; big data SQL experience is a plus).
• Experience with Linux OS (e.g., bash toolset and utilities).
• Proficiency with version control systems like Git, GitHub, or Azure DevOps.
• Strong problem-solving and debugging abilities.
• Commitment to software craftsmanship, adherence to Agile principles, and a pride in writing high-quality code.
• Skills in communicating technical concepts and changes to non-technical stakeholders.

Nice to Have

• Demonstrable work on platforms like Github, Kaggle, or StackOverflow.
• Cloud expertise, preferably in AWS and GCP.
• Experience deploying machine learning models in cloud environments.
• Familiarity with Large Language Models (LLMs).