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merry jake

@merryjake

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AI/ML engineer at Eli Lilly who cut incident handling time by 95% with Python automation.

India

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At Eli Lilly and Company, I built AI and automation initiatives, including a retrieval-augmented assistant over ServiceNow work notes that cut manual shift-handover effort by about 80%. I also integrated an enterprise LLM into an incident console and built Python services connecting ServiceNow, Teams, and SharePoint, reducing incident handling time from 15–20 minutes to under three.

For MedScan Intelligence, I built a multi-agent clinical RAG platform with hybrid retrieval, evaluation gates, and model routing. I improved answer faithfulness from 0.77 to 0.89, and developed a fine-tuned BioBERT model for entity extraction; at Deloitte, I built data pipelines for a cardiovascular risk classifier that reached 95% accuracy.

Experience

Work history, roles, and key accomplishments

Technology Intern

Eli Lilly and Company

Jan 2026 - Jul 2026 (6 months)

Scoped, designed, and built six AI and automation initiatives, including a retrieval-augmented assistant that cut manual shift-handover effort by ~80% and an incident console that reduced handling time from 15-20 minutes to under 3 minutes.

Python PostgreSQL ServiceNow REST APIs LLM Integrations RAG Data Profiling Natural Language Processing Human In The Loop Audit Logging

Data Science Simulation

BCG X

Jan 2025 - Dec 2025 (11 months)

Validated a price-sensitivity churn hypothesis across 14K customer records at 85% classifier accuracy by engineering 10+ behavioral and pricing features and ranking drivers through Random Forest feature-importance analysis. Translated model output into a client-ready retention recommendation.

Python Machine Learning Feature Engineering Random Forest Data Quality Data Profiling

AI/ML Capstone Project Intern

Deloitte

May 2025 - Jul 2025 (2 months)

Delivered a cardiovascular risk classifier at 95% accuracy, 12 points over baseline, by engineering Python data pipelines over 17GB of clinical signal data and cutting preprocessing runtime by 60%. Applied SHAP attribution to surface the five strongest predictive drivers.

Python Data Pipelines Machine Learning SHAP data preprocessing Clinical Data

Education

Degrees, certifications, and relevant coursework

Microsoft

Azure AI Fundamentals (AI-900), Azure AI

Azure AI Fundamentals (AI-900) certification in progress.

Manipal Institute of Technology

B.Tech, Computer Science & Engineering (Artificial Intelligence)

2022 - 2026

Grade: 8.0/10

Activities and societies: Minor in Data Analytics

Pursuing a B.Tech in Computer Science & Engineering with a focus on Artificial Intelligence, including a minor in Data Analytics and a CGPA of 8.0/10.