Analyst, Data Science & AI

Role Overview

Responsibilities

• Translate business challenges into measurable analytical problems.
• Explore, profile, and validate governed enterprise data.
• Develop reproducible feature engineering, training, validation, and scoring pipelines using Databricks and Azure.
• Establish analytical baselines and business performance measures.
• Build and validate models using cross-validation, back-testing, uncertainty analysis, and business-relevant metrics.
• Develop document-intelligence and RAG solutions with grounded outputs, citations, evaluation, guardrails, and human review.
• Develop forecasting and inventory-optimization solutions that account for intermittent demand, uncertainty, service levels, and operational constraints.
• Develop classification and risk models using approaches for imbalanced data, calibration, explainability, and cost-sensitive decisions.
• Operationalize models using MLflow, registries, automated testing, deployment controls, monitoring, drift detection, and retraining plans.
• Apply privacy, security, lineage, explainability, bias, robustness, auditability, and incident-response controls throughout the AI lifecycle.