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Christopher Taylor

@christophertaylor6

Data Scientist at NTT DATA building RAG services and AI agents that resolve 60% of first-line requests without a handoff.

United States

Message

At NTT DATA, I built generative AI assistants as agents in workflows that resolve 60% of first-line requests without a handoff. I also designed a RAG service over 18,000 policy documents, cutting lookup time by 84%.

I evaluated releases against 350 labeled cases and added prompt-injection tests that cut unsupported answers by 42%. I turned three proofs of concept into production services and optimized token spend by a third.

At Daugherty Business Solutions, I built shared semantic models for 40 reports and set governance rules for 25 tables that passed a client audit with no findings. Earlier, I connected Salesforce and Sage X3 extracts into a reporting model, replacing manual ETL and reducing manual work by 90%.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist | Senior Consultant

Current

NTT DATA

Jan 2025 - Present (1 year 9 months)

Built generative AI assistants as AI agents within agentic workflows that resolve 60% of first-line requests without a handoff. Designed a RAG service with embeddings in vector stores over 18,000 policy documents, cutting lookup time by 84%.

Generative AI AI Agents RAG Vector Stores Prompt Engineering Model Evaluation CI CD Cost Optimization Python PyTorch AWS Microsoft Fabric Power BI

Senior Consultant

Daugherty Business Solutions

Jan 2024 - Jan 2025 (1 year)

Built semantic modeling and report development on a shared dataset for 40 reports, with standardized business metrics defined once. Set data governance rules covering data classification and PII handling for 25 shared tables, which passed a client audit with no findings.

Semantic Modeling Data Governance Row level security Data Lineage Microsoft Fabric Power BI DAX Deployment pipelines SDLC Data Products

Consultant

Daugherty Business Solutions

Jan 2021 - Jan 2024 (3 years)

Built Power BI reports on manufacturing lead times and supplier delays for a supply chain client, cutting weekly planning prep by 6 hours. Added monitoring to nightly SQL and Python jobs so failures surfaced within 15 minutes instead of the next morning.

Power BI SQL Python Salesforce Sage X3 ETL Vector Databases Git Monitoring

Data Analyst | Internship

Public Partnerships | PPL

Jun 2020 - Dec 2020 (6 months)

Built a weekly Excel report that replaced a manual hours check, cutting preparation from 5 hours to 45 minutes. Cleaned 50,000 timesheet records with SQL, removing duplicates that had inflated weekly totals by 4%.

Excel SQL Data Cleaning Reporting