S&P Global, Inc.
Associate Director of Data Scientist – NLP, LLM and GenAI
S&P Global, Inc., Princeton, New Jersey, us, 08543
About the Role:
Grade Level (for internal use):
12 The Role:
Associate Director of Data Science – NLP, LLM and GenAI S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for hands-on ML scientists and NLP/Gen AI/LLM scientists to grow into the next step in their career journey and apply their technical expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research around LLMs, Gen AI, and related areas. Responsibilities: ML, Gen AI, NLP, LLM Model Development: Design and develop custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines. Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering and ensure the solution meets all technical and business requirements. Work closely with other members of data science, MlOps, technology teams in the design, development, and implementation of the ML model solutions. ML, NLP, LLM Model Evaluation: Work closely with the other data science team members to develop, validate, and maintain robust evaluation solutions and tools to evaluate model performance, accuracy, consistency, reliability, during development, UAT. 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. Documentation: Write and maintain comprehensive documentation of ML modeling processes and procedures for reference and knowledge sharing. Develop Models Based on Standards and Best Practices: Ensure that the models are designed and developed while adhering to specified standards, governance and best practices in ML model development as specified by senior Data Science and MLOps leads. Assist in Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. What We’re Looking For: Bachelor's / Master’s or Ph.D degree in Computer Science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field. 4+ 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 3+ years hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch or similar statistical tools. Expert in python programming. 3+ years hands-on experience developing natural language processing (NLP) models, ideally with transformer architectures. 3+ years of experience with implementing information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Knowledge of and measurable hands-on experience with developing or tuning Large Language Models (LLM) and Generative AI (GAI) 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 and/or participation in Kaggle competitions. Compensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $150,000 - $215,000. 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
. About S&P Global Ratings At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction. By bringing transparency to the market through high-quality independent opinions on creditworthiness, we enable growth across a wide variety of organizations, including businesses, governments, and institutions. S&P Global Ratings is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today.
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Grade Level (for internal use):
12 The Role:
Associate Director of Data Science – NLP, LLM and GenAI S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for hands-on ML scientists and NLP/Gen AI/LLM scientists to grow into the next step in their career journey and apply their technical expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research around LLMs, Gen AI, and related areas. Responsibilities: ML, Gen AI, NLP, LLM Model Development: Design and develop custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines. Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering and ensure the solution meets all technical and business requirements. Work closely with other members of data science, MlOps, technology teams in the design, development, and implementation of the ML model solutions. ML, NLP, LLM Model Evaluation: Work closely with the other data science team members to develop, validate, and maintain robust evaluation solutions and tools to evaluate model performance, accuracy, consistency, reliability, during development, UAT. 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. Documentation: Write and maintain comprehensive documentation of ML modeling processes and procedures for reference and knowledge sharing. Develop Models Based on Standards and Best Practices: Ensure that the models are designed and developed while adhering to specified standards, governance and best practices in ML model development as specified by senior Data Science and MLOps leads. Assist in Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. What We’re Looking For: Bachelor's / Master’s or Ph.D degree in Computer Science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field. 4+ 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 3+ years hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch or similar statistical tools. Expert in python programming. 3+ years hands-on experience developing natural language processing (NLP) models, ideally with transformer architectures. 3+ years of experience with implementing information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Knowledge of and measurable hands-on experience with developing or tuning Large Language Models (LLM) and Generative AI (GAI) 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 and/or participation in Kaggle competitions. Compensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $150,000 - $215,000. 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
. About S&P Global Ratings At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction. By bringing transparency to the market through high-quality independent opinions on creditworthiness, we enable growth across a wide variety of organizations, including businesses, governments, and institutions. S&P Global Ratings is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today.
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