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Lead Data Scientist

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Hybrid

Lead Data Scientist

Aspire Systems

Lead Data Scientist

Skills

SQL QueriesData EngineeringDeep LearningData MiningPythonTesting & QANumPypandasPyTorchTensorFlowMachine LearningAISupply Chain

9 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

16 October 2026

What they need


Experience: 5-10 Years

Location: Kochi, Chennai & Bangalore

JD

  • Core AI/ML: Expert-level proficiency in Python and leading AI/ML frameworks, including TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
  • Strong understanding of supervised, unsupervised, and deep learning techniques, with experience developing, evaluating, and optimizing production-grade machine learning models.
  • LLMs & Generative AI: Hands-on experience with transformer-based foundation models (GPT, Llama, BERT, Mistral, etc.), prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning (LoRA/QLoRA), embedding models, and agentic AI workflows for domain-specific applications.
  • Data Engineering: Proficiency in working with structured, semi-structured, and unstructured data (JSON, XML, CSV, Parquet, documents).
  • Strong knowledge of SQL/NoSQL databases, vector databases, and graph data structures. E
  • xperience with document processing, OCR pipelines, and specialized data extraction is a strong advantage.
  • Backend & AI Deployment: Experience exposing AI/ML models through

Roles and Responsibility

  • This role is not just about building AI modelsit is about building the intelligence that powers the industrial backbone of the future.
  • You will solve real-world, high-impact challenges, from ensuring product design and manufacturing are safe and compliant to predicting supply chain disruptions before they impact critical operations or national security capabilities.
  • Data Exploration & Analysis Regulatory Text Interpretation Rule Formalization Natural Language Querying Retrieval-Augmented Generation (RAG) & Knowledge Engineering Forecasting & Demand Prediction Classification & Risk Scoring Data Engineering for AI AI Model Orchestration Performance Optimization Model Validation & Quality Assurance

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