Rubeena Riyas

About

ML/data engineer who owned an end-to-end production sales analytics pipeline at 15,000+ user scale, delivering ~50% compute reduction, ~80% faster reporting, and ~$1.2M impact. Also shipped a production RAG-based AI assistant over internal BigQuery/docs with evaluation metrics and safety guardrails, and built shared Python libraries to standardize reliability and accelerate engineering teams.

Key Strengths

• Owned end-to-end production ML/data pipeline for sales analytics platform used by 15,000+ users
• Delivered major performance gains: ~50% compute time reduction and ~80% report speed improvement
• Drove ~$1.2M business impact through pipeline optimization and reliability improvements
• Deep expertise in data pipeline optimization (incremental processing, partitioning, predicate pushdown, Z-ordering, Spark tuning)
• Shipped production RAG assistant over internal sources (BigQuery + documentation) with evaluation and safety guardrails
• Balanced latency, cost, quality, and safety in production LLM systems (caching, smaller models, constrained queries, reduced tool calls)
• Built shared Python libraries with strong testing, versioning, and backward compatibility to improve team velocity and reliability

Experience

Education

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Languages