Chief Data Innovator

17 hours ago

Madurai, Tamil Nadu, India beBeeDataScientist Full time ₹ 15,00,000 - ₹ 20,00,000

We're seeking visionary data innovators to spearhead the development of cutting-edge machine learning models on Azure. As a data scientist, you'll be responsible for unlocking business value and driving innovation through AI.

Key Responsibilities
  • Create, deploy, and refine machine learning models on the Azure ecosystem to drive impactful solutions.
  • Analyze and extract insights from large unstructured datasets to inform scalable solution design.
  • Apply advanced natural language processing and generation techniques to tackle complex business challenges.
  • Leverage Azure-native services such as Copilot Studio, AI Foundry, and Genie AI in Databricks to deliver innovative AI-driven projects.
  • Collaborate with cross-functional teams to identify AI opportunities and develop effective solutions.
  • Stay up-to-date with new algorithms, tools, and frameworks to continuously improve model accuracy and performance.
  • Communicate findings and recommendations clearly to both technical and non-technical stakeholders.
  • Take ownership of end-to-end project delivery from data exploration to production deployment.
Required Skills & Qualifications
  • Demonstrated expertise 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 such as TensorFlow, PyTorch, Hugging Face, etc.
  • Prior experience with Copilot Studio, AI Foundry, Genie AI in Databricks is highly desirable.
  • Excellent problem-solving, analytical, and innovation skills.
  • Strong communication and storytelling ability to present AI solutions to stakeholders.
  • Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.
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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