Full-Time

Director of Data Science

NLP, LLM and GenAI

Confirmed live in the last 24 hours

S&P Global

S&P Global

10,001+ employees

Provides financial information and analytics services

Data & Analytics
Financial Services

Compensation Overview

$180k - $225kAnnually

+ Annual Incentive Plan

Senior

New York, NY, USA

Category
Applied Machine Learning
Natural Language Processing (NLP)
Data Science
AI & Machine Learning
Data & Analytics
Required Skills
Python
Data Science
Tensorflow
Git
Keras
Pytorch
Apache Spark
Natural Language Processing (NLP)
Requirements
  • 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.
Responsibilities
  • 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
  • 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
  • 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.
  • Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability.
  • 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.
  • Collaborate closely with business and PM stakeholders in roadmap planning and implementation efforts and ensure technical milestones align with business requirements.
  • 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.
  • Maintain comprehensive documentation of ML modeling processes and procedures for reference and knowledge sharing.
  • Ensure the use of standards, governance and best practices in ML model development, and adherence to model and data governance standards.
  • Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions.

S&P Global provides financial information and analytics to a wide range of clients, including investors, corporations, and governments. The company offers services such as credit ratings, market intelligence, and indices, which help clients understand and navigate the global financial market. S&P Global's products work by utilizing advanced data analytics and research to deliver insights that assist clients in making informed decisions and managing risks. Unlike many competitors, S&P Global has a diverse range of divisions, including S&P Global Ratings and S&P Global Market Intelligence, which allows it to cater to various financial needs. The company's goal is to support clients in driving growth while also committing to corporate responsibility and making a positive impact on society and the environment.

Company Stage

IPO

Total Funding

N/A

Headquarters

New York City, New York

Founded

N/A

Growth & Insights
Headcount

6 month growth

17%

1 year growth

6%

2 year growth

17%
Simplify Jobs

Simplify's Take

What believers are saying

  • S&P Global's strategic acquisitions and investments, such as in Novata, demonstrate a strong commitment to expanding sustainability solutions and enhancing their service offerings.
  • The launch of the India Research Chapter highlights S&P Global's focus on emerging markets, potentially leading to significant growth opportunities.
  • Their diverse revenue streams, including subscription-based models and transaction services, provide financial stability and resilience against market fluctuations.

What critics are saying

  • The integration of acquired companies like Visible Alpha may pose challenges in aligning technologies and cultures, potentially affecting service delivery.
  • The competitive landscape in financial analytics is intense, with rivals like Bloomberg and Moody's potentially eroding S&P Global's market share.

What makes S&P Global unique

  • S&P Global's comprehensive suite of services, including credit ratings, market intelligence, and indices, positions it as a one-stop solution for financial information and analytics, unlike competitors who may specialize in only one area.
  • Their commitment to corporate responsibility and ESG solutions sets them apart in the financial sector, appealing to clients focused on sustainable and ethical investing.
  • The acquisition of companies like Visible Alpha and World Hydrogen Leaders enhances S&P Global's capabilities in investment research and commodity insights, providing a competitive edge.

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