Lead Data scientist

Job Title

Lead Data scientist

Job title:

Lead Data scientist

1) ML & Deep Learning Model Development

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Design, train, and optimize ML models for prediction, classification, ranking, time-series forecasting, anomaly detection, NLP, and recommendation use cases.

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Build robust experimentation workflows (train/validation strategy, ablations, error analysis) and improve model quality through iterative tuning.

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2) GenAI Engineering (LLMs, RAG / MCP / fine-tuning, Agents)

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Build enterprise-grade LLM applications using RAG (retrieval-augmented generation), MCP, and fine-tuning approaches: chunking strategies, embedding generation, hybrid retrieval, reranking, prompt templates, and citation/attribution patterns.

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Develop LLM applications with tool use/function calling patterns and agentic workflows where appropriate.

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3) ML & LLM Operations: Productionization, Deployment & Monitoring

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Deploy and operate real-time and batch inference solutions on Azure using managed endpoints and/or containerized serving.

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Build CI/CD for ML systems: automated packaging, container builds, model validation tests, staged rollouts, and rollback strategies.

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Establish lifecycle management: model registry/versioning, lineage, promotion workflows, and release governance.

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4) Pipeline Orchestration & Automation (Train → Deploy)