Highly Skilled Data Scientist Required

18 hours ago


Thāne, Maharashtra, India beBeeData Full time ₹ 2,50,00,000 - ₹ 3,00,00,000
Job Description

We are seeking highly skilled and innovative Data Scientists to join our team.

  • The ideal candidates will bring deep experience in building and deploying advanced machine learning and AI models, particularly working with unstructured data, NLP, and generative AI solutions.

Key Responsibilities:

  • Design, develop, and deploy ML and AI models on the Azure ecosystem.
  • Work extensively with unstructured data sets (text, images, documents, etc.) to extract insights and build scalable solutions.
  • Apply advanced Natural Language Processing (NLP) and Natural Language Generation (NLG) techniques to solve business problems.
  • Leverage Copilot Studio, AI Foundry, Genie AI in Databricks, and other Azure-native services for generative AI use cases.
  • Collaborate with cross-functional teams to identify AI opportunities and deliver impactful solutions.
  • Continuously explore, test, and implement new algorithms, tools, and frameworks to improve model accuracy and performance.
  • Communicate findings and recommendations effectively to both technical and non-technical stakeholders.
  • Take ownership and accountability for end-to-end project delivery, from data exploration to production deployment.

Required Skills & Qualifications:

  • Proven hands-on experience in Azure Machine Learning, Azure AI services, and Databricks.
  • Strong background in NLP, NLG, LLMs, and generative AI frameworks.
  • Experience with unstructured data pipelines and feature engineering.
  • Proficiency in Python, PySpark, and ML libraries (TensorFlow, PyTorch, Hugging Face, etc.).
  • Practical experience with Copilot Studio, AI Foundry, Genie AI in Databricks is highly desirable.
  • Strong problem-solving, analytical, and innovation skills.
  • Excellent communication and storytelling ability to present AI solutions to stakeholders.

PREFERRED QUALIFICATIONS:

  • Experience in building and deploying enterprise-grade AI solutions in cloud-native environments.
  • Prior exposure to GenAI-based copilots, conversational AI, or knowledge assistants.
  • Familiarity with MLOps frameworks for productionizing AI models.


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