[Hiring] Lead Data Scientist @S&P Global

Role Description

Standard & Poor’s Financial Services LLC seeks a Lead Data Scientist responsible for leading the design and development of custom machine learning, Generative AI (GAI), Natural Language Processing (NLP), and Large Language Models (LLMs) for both batch and streaming AI/ML pipelines.

• Architect solutions covering data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), fine-tuning, and prompt engineering.
• Utilize industry-standard tools and frameworks including Python, PyTorch, and Hugging Face Transformers for model development & finetuning.
• Work closely with cross-functional teams including data science, MLOps, and technology groups to align solutions with technical and business requirements.
• Collaborate with data science teams to design and implement robust evaluation frameworks that measure model performance, accuracy, consistency, and reliability during both development and UAT stages.
• Monitor and apply model optimizations to enhance system efficiency and ensure continuous improvement.
• Partner with engineering teams to deploy models into production environments, ensuring high reliability, scalability, and performance of deployed systems.
• Deploy and manage AI applications on cloud platforms, such as AWS, Google Cloud, or Microsoft Azure.
• Develop and maintain comprehensive documentation of all ML modeling processes and procedures, ensuring reproducibility and effective knowledge sharing across teams.
• Ensure all models are developed in adherence to established standards, governance frameworks, and best practices as defined by senior Data Science and MLOps leadership.
• Lead efforts to troubleshoot complex issues in ML model development and data pipelines, devising innovative solutions to enhance system robustness and performance.

Qualifications

• Master’s degree in Computer Science, Data Science, or a related IT field.
• 3 years of experience in the job offered or related occupation.
• 3 years of experience must include:
• Python programming, machine learning frameworks and statistical libraries, including PyTorch, Hugging Face Transformers, and LangChain.
• Large Language Model (LLM) architectures including transformer-based models, such as GPT, BERT, or T5.
• Training, fine-tuning, and adapting large-scale LLMs for domain-specific applications.
• Developing Natural Language Processing (NLP) solutions using traditional and transformer-based architectures.
• Text generation, summarization, classification, question answering, and entity extraction as part of implementing scalable information retrieval systems.
• Traditional keyword-based search and semantic search approaches using vector embeddings and approximate nearest neighbor techniques.
• Open Source and research contributions related to machine learning or Artificial Intelligence.
• Scoping, formulating, and executing complex machine learning projects, including stakeholder management.

Requirements

• The anticipated base salary range for this position is $189,532 to $206,350.
• Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses & certifications.
• This role is eligible for an annual incentive plan.
• This role is eligible to receive additional S&P Global benefits.

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.