Lead Data Scientist

13 hours ago

Hyderabad, Telangana, India Talent Hired-the Job Store Full time ₹ 15,00,000 - ₹ 25,00,000 per year

We are looking for a highly skilled Lead Data Scientist to drive end-to-end data science initiatives from hypothesis-driven modeling and statistical validation to cloud-native deployment and next-gen Agentic AI systems. The ideal candidate has a strong foundation in statistics, expertise in Azure cloud architecture, and experience in deploying and monitoring machine learning models at scale. Familiarity with LLM orchestration frameworks such as LangChain, AutoGen, or ReAct is a must.

Key Responsibilities:

Data Science & Statistical Modeling

  • Lead the design of experiments using hypothesis testing, confidence intervals, p-values, and other inferential methods.
  • Guide the team on bias-variance trade-offs, model selection, and validation strategies like k-fold cross-validation, stratified sampling, etc.
  • Build scalable ML models for structured and unstructured data using Python, Scikit-learn, PyTorch, or TensorFlow.

Cloud & Deployment (Azure Focused)

  • Architect ML solutions on Azure, leveraging services such as Azure ML, Azure Functions, AKS, and Azure Blob/Data Lake.
  • Design and implement deployment pipelines for both batch and real-time inference use cases.
  • Develop and manage containerized services (Docker, Kubernetes) and robust API endpoints for ML integration.
  • Handle model packaging, versioning, and rollback strategies for safer deployments.
  • Set up end-to-end monitoring systems for drift detection, model accuracy tracking, and performance logging.

Agentic AI & LLM Orchestration

  • Build and orchestrate Agentic AI frameworks using LangChain, CrewAI, AutoGen, or AutoGPT.
  • Apply ReAct patterns for chaining reasoning and tool usage.
  • Design LLM agents with memory systems, reasoning loops, and multi-agent coordination for complex workflows.
  • Use LLMs as orchestrators, integrating APIs, databases, and external tools.

Required Skills & Experience:

  • 10+ years of experience in data science and ML, with 3+ years in a leadership or technical mentorship role.
  • Strong statistical background: hypothesis testing, confidence intervals, p-values, A/B testing, etc.
  • Hands-on expertise with Azure cloud services for data engineering, modeling, and deployment.
  • Proven track record of deploying machine learning models in production (batch and real-time).
  • Experience with Docker, Kubernetes, and RESTful API development.
  • Proficiency in Python, and experience with frameworks like Scikit-learn, XGBoost, TensorFlow, or PyTorch.
  • Hands-on knowledge of LangChain, ReAct, or other LLM orchestration frameworks.
  • Strong understanding of LLM tool usage, reasoning loops, and agent-based design patterns.

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