Lead Data Scientist

2 weeks ago

Chennai, Tamil Nadu, India Chargeback Gurus Fintech Pvt Ltd Full time ₹ 12,00,000 - ₹ 36,00,000 per year
  • Lead the design and implementation of enterprise-grade Machine Learning, Deep Learning and Generative AI solutions.
  • Define and execute the AI technology projects, aligning Generative AI, Machine Learning, and Deep Learning initiatives with business strategy and data architecture.
  • Design, evaluate, and guide development of autonomous and Agentic AI systems capable of reasoning, planning, and tool-based decision-making.
  • Architect end-to-end RAG pipelines – including document processing, embedding generation, vector storage, retrieval mechanisms, and contextual response systems.
  • Oversee Machine Learning and Deep Learning model development, training, deployment, and optimization for predictive and generative use cases.
  • Establish robust LLMOps / MLOps pipelines ensuring model lifecycle management, observability, version control, and performance monitoring.
  • Collaborate with data engineering, analytics, and DevOps teams to integrate AI systems with enterprise data warehouse/lakes, APIs, and reporting environments.
  • Work with stakeholders to identify, evaluate, and prioritize AI-driven business opportunities, focusing on measurable impact and innovation.
  • Provide technical leadership, mentorship, and guidance to AI engineers, data scientists, and developers, fostering a high-performance innovation culture.
  • Stay ahead of emerging AI research, frameworks, and tools, driving continuous evolution of enterprise AI capabilities.


Requirements

Core Skills

  • Deep knowledge in Generative AI, Large Language Models (GPT, Claude, Llama, Mistral, etc.), and RAG architectures.
  • Strong proficiency in Agentic AI concepts — autonomous agents, multi-agent orchestration, and reasoning loops.
  • Advanced understanding of Machine Learning (ML) and Deep Learning (DL) algorithms, architectures (Transformers, CNNs, RNNs), and model deployment workflows.
  • Experience in implement solutions using LLM, AWS Agentic AI framework, LangChain, LlamaIndex or similar frameworks.
  • Hands-on experience with RDBMS, No SQL and vector databases
  • Proficiency in Python, scikit-learn, PyTorch, TensorFlow, and Hugging Face Transformers.
  • Expertise in LLMOps / MLOps practices – model training, CI/CD, observability, and drift management.
  • Deep understanding of cloud-native AI development tool (AWS Sagemaker, Azure AI, GCP Vertex AI).
  • Excellent leadership, communication, and stakeholder management skills to align AI initiatives with business goals.

Good-to-Have Skills:

  • Experience in Data Engineering – ETL/ELT pipeline design, data modeling, data warehousing, and integration with AI pipelines.
  • Familiarity with Data Visualization and BI tools such as Power BI, Tableau, Amazon QuickSight especially for building analytical insights from AI-driven data.
  • Understanding of DataOps and analytics architectures supporting AI and decision intelligence systems.
  • Knowledge of enterprise data platforms and API-based data integration to connect AI models with structured and unstructured data sources.


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