Data Scientist
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The role
Lead the development and integration of AI technologies into client services operations, focusing on generative AI, MLOps, and model fine-tuning.
Build production-grade AI services: LLM-based apps, RAG pipelines, recommendations, forecasting, and classification.
Develop and maintain data models and schemas optimized for analytics, ML feature stores, and AI workloads.
Deliver end-to-end data and AI projects: ingestion, modeling, pipeline development, feature engineering, model training, deployment, and monitoring.
Apply best practices in data architecture, governance, and MLOps; implement data validation and model evaluation at each stage.
Collaborate with cross-functional teams, translate requirements into scalable AI solutions, communicate clearly to technical and non-technical audiences, and stay aligned with Agile practices.
Build production-grade AI services: LLM-based apps, RAG pipelines, recommendations, forecasting, and classification.
Develop and maintain data models and schemas optimized for analytics, ML feature stores, and AI workloads.
Deliver end-to-end data and AI projects: ingestion, modeling, pipeline development, feature engineering, model training, deployment, and monitoring.
Apply best practices in data architecture, governance, and MLOps; implement data validation and model evaluation at each stage.
Collaborate with cross-functional teams, translate requirements into scalable AI solutions, communicate clearly to technical and non-technical audiences, and stay aligned with Agile practices.
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