Himanshu Karu
Consultant - Statistical Data and Analytics @Eli Lilly and Company
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WORK HISTORY
Consultant - Statistical Data and Analytics @Eli Lilly and Company
Lead for the Immunology RWE portfolio, aligning studies with scientific and brand strategies.• Built Python-based validation frameworks and feasibility tools covering 135+ RWD assets.• Applied advanced survival analytics, including Kaplan–Meier estimation and Cox proportional hazards modelling, to support evidence generation and publication-focused analyses.• Built a Python-based RAG LLM to assist ETL workflows by extracting and mapping unstructured data to structured outputs using enterprise data assets and their data dictionary as retrieval context.• Developed a BERT-based NLP pipeline to extract PICO (Population, Intervention, Comparator, Outcomes) from clinical trial abstracts to support Network Meta-Analysis (NMA) for comparative evidence synthesis.• Built linear regression–based dose and days-of-supply imputation for pharmacy claims to support early uptake, adherence, and discontinuation analyses for a newly launched product.• Created and CI/CD-enabled dashboards covering 72M+ patients using Microsoft Fabric (Power BI), with fully automated weekly refreshes and minimal manual intervention, enabling faster, decision-ready insights to support business decision-making.• Led cross-functional training (Let’s Learn Fridays) on Microsoft Fabric (Power BI) for over 75 participants.
EDUCATION
Indian Institute of Technology (Banaras Hindu University), Varanasi
B.Tech, Pharmacy, Pharmaceutical Sciences, and Administration
ABOUT HIMANSHU KARU
I’m a Data Science professional with 6.5+ years of experience in the healthcare and life sciences domain, working at the intersection of real-world evidence (RWE), machine learning, and Generative AI to solve complex, high-impact business problems.My work spans LLM- and GenAI-based applications, deep learning, and classical ML/NLP, with hands-on experience taking solutions from problem framing and data engineering to modeling, validation, and production deployment. I’ve worked extensively with large-scale healthcare data (claims, EHR, and observational datasets) to support medical affairs, clinical development, and strategic decision-making across global geographies.I’m particularly interested in building practical, scalable AI solutions—from advanced analytics and survival modeling to GenAI systems that improve insight discovery, automation, and stakeholder productivity. I value clarity in communication, strong engineering fundamentals, and data science that actually moves the needle for the business.I hold an engineering degree from IIT (BHU), Varanasi, and enjoy working in environments where technical depth, ownership, and real-world impact matter.
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