Senior Data Scientist (GenAI)

• Detail-oriented, hands-on, and metric-driven.
• Curious about LLMs, vector search, and retrieval systems.
• Collaborative with engineers, ETL teams, and business users.
• Comfortable designing evaluation pipelines and experiments.
• Strong communicator: turns feedback into actionable insights

• Define evaluation sets across clients, content types, and languages.
• Build labelling pipelines and dashboards for manual or UI-based feedback.
• Measure and tune hybrid retrieval (semantic + keyword), top-k, rerankers, and filters.
• Evaluate embedding models and chunking strategies for accuracy and coverage.
• Assess LLM answer quality: grounded factuality, hallucination rate, completeness.
• Analyze failure patterns across queries, long contexts, attachments vs. emails.
• Collaborate with backend, ETL, and frontend teams to align telemetry, schema, and feedback capture.
• Translate user feedback into actionable metrics and backlog items.
• Evaluate cost/performance trade-offs for summarization, spillover, and indexing.​​​​​​

• Applied ML/Data Science with strong evaluation discipline.
• Python (pandas, Jupyter/Notebooks) + SQL.
• Information retrieval / RAG evaluation: Recall@K, MRR, nDCG, citation grounding.
• Experience with LLMs: prompting, grounding, long-context handling, cost/latency awareness.
• Building reproducible pipelines and dashboards.
• Strong communicator: translating business questions into metrics and experiments.

• Hands-on with Azure AI Search vector/hybrid tuning, index schema.
• Experience designing human-in-the-loop annotation pipelines.
• Knowledge of enterprise access-control / security trimming.
• Experience tracking embedding drift and retrieval failures.
• Working with large-scale document/email datasets.

If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics.

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