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Lead Data Scientist @ S&P Global

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 Lead Data Scientist

Job Description

The Team:

  • As a member of the Commodity Insights you will work on building and deploying ML/LLM powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients.
  • You will be responsible for the management, deployment and optimization of ML Models and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative.

Whats in it for you:

  • Exciting tasks and the team with own product development in the space of intelligent data solutions based on Machine Learning

Responsibilities:

  • Play a central role in all stages of the AI product development life cycle, including:
    • Designing Machine Learning systems and model scaling strategies
    • Research & Implement ML and Deep learning algorithms for production
    • Run necessary ML tests and benchmarks for model validation
    • Fine-tune, retrain and scale existing model deployments
    • Extend existing ML librarys and write packages for reproducing components
    • Partner with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
    • Interpret results and present them to business leaders
    • Manage production pipelines for enterprise scale projects
    • Perform code reviews & optimization for your projects and team
    • Lead and mentor by example, including project scrums

Technical Requirements:

  • Proven track record as a ML engineer
  • Expert proficiency in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.)
  • Excellent exposure to large scale model deployment strategies and tools
  • Excellent knowledge of ML & Deep Learning domain
  • Solid exposure to Information Retrieval, Web scraping and Data Extraction at scale
  • Knowledge in AWS Technologies: Terraform, CFT, Lambda, Fargate, ECS and also in SQL, containerization and Django.
  • Experience with SOTA models related to NLP like Classification, Summarization, Phrase extraction, Table Extraction and OCR
  • Open to learning new technologies and programming languages as required
  • Knowledge in model monitoring and retrain & tuning of models

Good to have:

  • 4+ years of relevant experience in ML Engineering
  • Prior substantial experience regarding document processing

Job Classification

Industry: Banking
Functional Area / Department: Data Science & Analytics,
Role Category: Data Science & Machine Learning
Role: Data Scientist
Employement Type: Full time

Contact Details:

Company: S&P Global Market
Location(s): Hyderabad

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Keyskills:   Python Pytorch Sklearn Pandas Spacy AWS

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S&P Global

S&P Capital IQ, a business line of The McGraw-Hill Companies (NYSE:MHP), is a leading provider of multi-asset class and real time data, research and analytics to institutional investors, investment and commercial banks, investment advisors and wealth managers, corporations and universities aroun...