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Experience:
4–6+ years delivering end-to-end data science projects.
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Education:
Master’s or PhD in Data Science, Machine Learning, Statistics, Computer Science, Applied Mathematics, or related quantitative field (required from this level onward).
• Core stack: Python, Spark, Git; ML frameworks; Databricks/MLflow (or equivalent); cloud basics.
• Translate business needs into ML/AI problem statements and measurable success metrics.
• Develop ML models and, where relevant, GenAI components (e.g., retrieval-augmented generation, prompt pipelines) with transparent evaluation criteria.
• Run evaluation: offline metrics, error analysis, bias checks, and monitoring baselines; document decisions and assumptions.
• Communicate results and limitations clearly to technical and non-technical stakeholders; support adoption in workflows.




• Python (pandas, numpy) + Git for reproducible development
• Databricks (Notebooks, Workflows) for development and orchestration
• ML flow (experiments, tracking, model registry) for lifecycle management
• Azure (cloud services; where relevant Azure OpenAI and Azure AI Foundry for GenAI build/evaluation)
• Databricks Mosaic AI (including Mosaic AI Model Serving) for GenAI delivery in the lakehouse
• Databricks Vector Search for RAG retrieval patterns
• Unity Catalog for governed data and model access (where applicable)
• Lakehouse Monitoring / model monitoring for quality and drift (where applicable)

📌 Data Scientist (Hyderabad)
🏢 Infosys
📍 Hyderabad