Data Scientist III

As a Data Scientist III at S&P Global, your role will involve helping to build and optimize the data infrastructure that supports analytics and machine learning solutions across the organization. You will collaborate with colleagues from data science, engineering, and business teams to deliver scalable, reliable, and cloud-enabled data solutions. **Key Responsibilities:**

• Collaborate with stakeholders to understand data needs and translate them into actionable technical requirements. - Design, build, and maintain scalable data pipelines using modern tools and cloud platforms like AWS, Azure, or GCP. - Develop and maintain data infrastructure for analytics and machine learning, leveraging cloud-native technologies and services. - Improve data quality, lineage, and reliability, and troubleshoot issues across the data lifecycle. - Support the deployment and monitoring of analytics and ML solutions in production, working closely with data science and engineering peers. - Contribute to an Agile team environment, including documentation, code reviews, and iterative delivery. **Qualifications Required:**
• University degree in Computer Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience). - 5+ 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 like PyTorch, TensorFlow, Keras, scikit-learn. - 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 to model deployment, emphasizing model performance, robustness, and maintainability. - Working knowledge of data storage and querying technologies like SQL and/or NoSQL. - Hands-on experience using cloud platforms for machine learning experimentation, training at scale, and model deployment. - Familiarity with distributed and accelerated computing concepts relevant to ML workloads. - Experience collaborating closely with data engineers and platform teams to integrate models into production pipelines. - Exposure to workflow orchestration or experiment management tools for reproducible ML pipelines. - Familiarity with version control systems like Git and best practices for collaborative ML development. - Strong ability to communicate results, trade-offs, and limitations of ML models clearly to both technical and non-technical stakeholders. In addition to the above qualifications, it is nice to have experience with data governance practices and improving data observability. Working at S&P Global Energy, you will be part of a division that provides a comprehensive view of global energy and commodities markets, enabling customers to make superior decisions and create long-term, sustainable value. S&P Global Energy is committed to Advancing Essential Intelligence through world-leading benchmarks, data, and insights. Joining S&P Global means being part of a diverse and inclusive team that values different perspectives and backgrounds. You will have access to various benefits including health & wellness programs, continuous learning opportunities, retirement planning, family-friendly perks, and more. If you are a US candidate and require an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com. S&P Global is dedicated to providing equal opportunities to all qualified candidates. As a Data Scientist III at S&P Global, your role will involve helping to build and optimize the data infrastructure that supports analytics and machine learning solutions across the organization. You will collaborate with colleagues from data science, engineering, and business teams to deliver scalable, reliable, and cloud-enabled data solutions. **Key Responsibilities:**