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Data Science Engineer-III

Noida, UP, IN

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Tools in this posting

  • Python
  • pandas
  • PySpark
  • SQL
  • AWS
  • Google Cloud (GCP)
  • Azure
  • BigQuery
  • scikit-learn
Source — Tool mentions in context
Advanced Modeling & AI Development Apply rigorous statistical and machine learning techniques to analyze billions of workforce management and HCM records and identify meaningful product and feature opportunities Develop and deploy modern Data Science/AI solutions including generative AI applications, RAG systems, and agentic workflow Establish evaluation frameworks to measure model quality and business impact Production AI System Ownership Lead the research, design, and implementation of end-to-end ML/AI pipelines in development and production environments Own the full model lifecycle: validation, deployment, monitoring, and iteration Ensure reliability, performance, and maintainability of AI systems in partnership with engineering teams Write high-quality, modular production code and design clean data/model pipelines Collaborate with engineering partners on CI/CD, observability, and scaling strategies Partner with Product Managers and domain experts to translate business requirements into scalable solutions Communicate model outcomes and insights effectively to technical and non-technical stakeholders Mentor junior data scientists through code reviews, model reviews, and modeling best practices Proactively identify opportunities to improve team capabilities and development standards Advanced degree (MS or PhD) in a quantitative field or equivalent industry experience 5-7+ years' experience in a software product environment, with at least 3 years' hands-on experience as a Data Scientist. Proven experience in building, training, and deploying ML models in a production environment. Deep familiarity with Python (pandas, scikit-learn, PySpark), SQL/BigQuery, and version control Hands-on experience with cloud-based ML infrastructure (AWS/GCP/Azure) and MLOps workflows Strong understanding of statistical modeling, experimentation, and evaluation frameworks Deep expertise in one or more ML domains such as NLP, deep learning, time-series, or clustering Hands-on experience building services and solving problems using LLMs and generative AI techniques preferred Ability to operate independently, think strategically, ensure execution and influence others Proven ability to effectively communicate with all levels of the organization

Job description

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Advanced Modeling & AI Development Apply rigorous statistical and machine learning techniques to analyze billions of workforce management and HCM records and identify meaningful product and feature opportunities Develop and deploy modern Data Science/AI solutions including generative AI applications, RAG systems, and agentic workflow Establish evaluation frameworks to measure model quality and business impact Production AI System Ownership Lead the research, design, and implementation of end-to-end ML/AI pipelines in development and production environments Own the full model lifecycle: validation, deployment, monitoring, and iteration Ensure reliability, performance, and maintainability of AI systems in partnership with engineering teams Write high-quality, modular production code and design clean data/model pipelines Collaborate with engineering partners on CI/CD, observability, and scaling strategies Partner with Product Managers and domain experts to translate business requirements into scalable solutions Communicate model outcomes and insights effectively to technical and non-technical stakeholders Mentor junior data scientists through code reviews, model reviews, and modeling best practices Proactively identify opportunities to improve team capabilities and development standards Advanced degree (MS or PhD) in a quantitative field or equivalent industry experience 5-7+ years' experience in a software product environment, with at least 3 years' hands-on experience as a Data Scientist. Proven experience in building, training, and deploying ML models in a production environment. Deep familiarity with Python (pandas, scikit-learn, PySpark), SQL/BigQuery, and version control Hands-on experience with cloud-based ML infrastructure (AWS/GCP/Azure) and MLOps workflows Strong understanding of statistical modeling, experimentation, and evaluation frameworks Deep expertise in one or more ML domains such as NLP, deep learning, time-series, or clustering Hands-on experience building services and solving problems using LLMs and generative AI techniques preferred Ability to operate independently, think strategically, ensure execution and influence others Proven ability to effectively communicate with all levels of the organization

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Noida, UP, IN

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First seen by us
Sep 4, 2026
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Last seen by us
Oct 9, 2026

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