Machine Learning Researcher working with a diverse team to integrate ML techniques into fusion technology. Collaborating with scientists and engineers to drive innovative energy solutions.
About the role
- Lead AI Researcher enhancing AI expertise related to credit risk for S&P Global. Collaborate with stakeholders on AI advancements and develop innovative solutions in a hybrid work environment.
Responsibilities
- Serve as a domain expert on Generative and Agentic AI for Credit Solutions.
- Attain fluency in AI applications, including the use of open-source and internal tools, to enhance AI expertise within Credit Solutions.
- Utilize internal and external AI applications offered by S&P Global to support credit risk analysis and decision-making.
- Closely monitor emerging technologies, industry adoption, and associated risks, including strengths, limitations, and regulatory guidelines concerning Gen-AI in credit risk.
- Develop and test new credit risk use cases utilizing data and AI applications within S&P Global across multiple platforms, including data wrangling and cross-referencing.
- Analyze quantitative and qualitative data from various content sets linked to credit ratings within S&P Global to understand their contributions to credit risk surveillance and risk management workflows.
- Collaborate with the Credit Solutions Thought Leadership team to develop and work on internal applications within a sandbox environment.
- Author thought leadership content independently and represent S&P Global at webinars and conferences, focusing on AI advancements in credit risk management.
Requirements
- Master’s or Ph.D. degree in Data Science, Statistics, Quantitative Finance, Artificial Intelligence, or a related quantitative/computational field.
- 5-10 years of relevant experience in AI/ML, quantitative roles, or data science.
- Ph.D. graduates in a statistics/data science/quant finance discipline from an internationally accredited university with hands-on experience in Gen-AI projects may be considered with 0-5 years of experience.
- Proficient in Python, R, and SQL.
- Experience in accessing data via feeds, cloud, or REST API preferred.
- Familiarity with GenAI frameworks (e.g., RAG, Agentic AI) and libraries including Hugging Face, TensorFlow, PyTorch, or Scikit-learn preferred.
- Prior experience in developing predictive analytics, data wrangling of structured and unstructured data, Natural Language Processing, or other emerging AI and automation use cases in financial services.
- Some knowledge of testing and validating AI models using techniques such as cross-validation, A/B testing, and performance metrics.
- Strong communication skills with a proven ability to solve problems and engage effectively across functions.
- Self-starter with a proactive mindset, capable of working independently across multiple groups and stakeholders.
Benefits
- Health & Wellness: Health care coverage designed for the mind and body.
- Flexible Downtime: Generous time off helps keep you energized for your time on.
- Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
- Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
- Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
- Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.
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