Director of Data Science – NLP, LLM and GenAI

Key Skills

Aartificial intelligence, Data science techniques, HuggingFace, Keras software library, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow

Job Description

The Team: The Data Science COE at S&P Global is looking for a hands-on Director of Data Science – NLP, LLM and GenAI to lead Data Science and Machine Learning Modeling strategy and solutions. This role will lead, implement, and define the Data Science, Gen AI, and LLM algorithms and model development strategy, and design and develop ML/NLP/LLM/GAI models and solutions while working with a broad range of partners across data, technology and business teams.

The Impact: In this role, you will play a pivotal role in leading and implementing our NLP, LLM and GenAI machine learning strategy and modeling, ensuring the seamless modeling and algorithm development of our machine learning models and data science solutions. As a Senior ML and Data Science Leader, you will lead ML, NLP, and LLM model development initiatives, mentor junior team members, and contribute to the strategic direction of our ML and data science efforts. You will be instrumental in leading strategic direction for ML, NLP, LLM, algorithm development in a world class AI ML team while working alongside well-known experts and researchers in AI ML modeling, ML engineers and data science and data engineering teams. You will contribute to setting roadmaps for AI ML model development and be a critical part of leading S&P’s AI-driven transformation to drive value internally and for our customers.

What’s in it for you: S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a ML Data Science team. The ideal candidate must have deep design and hands-on development expertise in ML, LLMs, model development and integrating ML solutions with business functions to create the next generation of AI-powered capabilities.

Responsibilities:

• ML, Gen AI, NLP, LLM Strategy: Develop and implement ML modeling and LLM development and fine-tuning strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Develop roadmap and strategy for NLP, LLM, Gen AI model development and lifecycle implementation

• ML, Gen AI, NLP, LLM Model Design and Development: Responsible for the design and development of custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines including data ingestion, preprocessing modules, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development and ensure the end-to-end solution meets all technical and business requirements, and SLA specifications. Work closely with members of technology and business leads and their teams in the design, development, and implementation of the ML model solutions
• ML, NLP, LLM Model Evaluation: Work closely with the MLOps team to create and maintain robust evaluation solutions and tools to evaluate model performance, accuracy, consistency, reliability, during development, UAT. Identify and implement model optimizations to improve system efficiency.
• NLP, LLM, Gen AI Model Deployment: Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability.
• Internal Collaboration: Collaborate closely with product teams, business stakeholders, MLOps, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.

• Stakeholder Engagement and Collaboration: Collaborate closely with business and PM stakeholders in roadmap planning and implementation efforts and ensure technical milestones align with business requirements.

• Mentorship: Recruit, develop and mentor technical AI/ML, NLP, LLM, Gen AI talent on the team Provide guidance and mentorship to junior ML scientists, fostering their professional growth and development.

• Documentation: Maintain comprehensive documentation of ML modeling processes and procedures for reference and knowledge sharing.

• Standards and Best Practices: Ensure the use of standards, governance and best practices in ML model development, and adherence to model and data governance standards.

• Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions.

What We’re Looking For:

• Ph.D (preferred), Bachelor's or Master's degree in Computer Science, Mathematics or Statistics , Computational linguistics, Engineering, or a related field.
• 7+ years of professional hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions.
• Demonstrated 4+ years hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark or similar statistical tools. Expert in python programming.
• 4 or more years project leadership experience including Agile project management, Scaled Agile Frameworks (SAFE)
• 5+ years hands-on experience developing natural language processing (NLP) models, ideally with transformer architectures.
• 5+ year’s experience with implementing information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings.
• Strong knowledge of and measurable hands-on experience with developing or tuning Large Language Models (LLM) and Generative AI (GAI)
• Experience in creating reports, projections, models, and presentations to support business goals and outcomes.
• Ability to exercise independent judgment and decision making on complex issues regarding initiatives, technical and business goals and related tasks.
• Experience with mentoring junior ML scientists,
• Ability to works under minimal supervision, using independent judgment.
• Excellent written & verbal communication and stakeholder management skill
• Strategic thinker and influencer with demonstrated technical and business acumen and problem-solving skills.
• Experienced with NLP, LLMs (extractive and generative), fine-tuning and LLM model development. Strong familiarity with higher level trends in LLMs and open-source platforms
• Nice to have: Experience with contributing to Github and open source initiatives or in research projects

Compensation/Benefits Information (US Applicants Only):

S&P Global states that the anticipated base salary range for this position is $180,000 - $225,000. Final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role.

In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.

This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.