Data Scientist

9 - 14 years

7 - 12 Lacs

Posted:-1 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description


  • Execute end-to-end Data Science projects including data collection, preprocessing, feature engineering, modelling, evaluation, and deployment.
  • Design and implement advanced Machine Learning algorithms (classification, regression, clustering, ensemble methods) and Natural Language Processing algorithms (Knowledge Graphs, Topic Modelling, Feature Extraction, Sentiment Analysis, BERT etc.)
  • Develop and deploy Generative AI and LLM-based solutions using platforms like OpenAI, Hugging Face, and LLama.
  • Apply Agentic AI frameworks such as LangChain, LangGraph, Crew AI, or Microsoft Semantic Kernel to build intelligent applications.
  • Proficient in designing and deploying scalable machine learning solutions using cloud architectures, with hands-on experience in at least one major platform (Azure, AWS, GCP, or IBM Cloud). Skilled in leveraging Databricks, ML platforms, managed databases, web hosting services, and document AI tools for end-to-end solution development.
  • Collaborate with business stakeholders to define problem statements, deliver insights, and drive impact.
  • Maintain reproducibility and version control using Git, GitHub
  • Effectively communicate technical concepts and project outcomes to both technical and non-technical stakeholders.

  • Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise
  • 7–9 years of hands-on experience in Data Science, Machine Learning, Deep Learning, and NLP in a production environment.
  • 2+ years of applied experience in Generative AI and LLMs (e.g., OpenAI, LLama).
  • Proficiency in agentic AI development using frameworks like LangChain, LangGraph, or similar.
  • Strong programming skills in Python and experience with ML/DL libraries
  • Experience deploying models via REST APIs or web applications.
  • Proficient in SQL for data extraction, transformation, and analysis.
  • Experience working with large datasets, feature engineering, and data preprocessing pipelines.
  • Solid understanding of model evaluation, cross-validation, and performance metrics.
  • Experience in MLOps, including model testing, deployment pipelines, governance frameworks, and continuous monitoring for reliable and compliant machine learning operations.
  • Experience with cloud ML pipelines and services (proficiency in at least one of Azure, AWS, GCP & IBM Cloud).
  • Strong interpersonal and client communication skills.
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