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Vaibhav Jain

@vaibhavjain5

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Data Scientist focused on LLM evaluation, RAG, and applied ML for business impact.

India

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What I'm looking for

I’m seeking DS/ML roles where rigorous experimentation and production-grade system thinking drive real business outcomes—especially work involving evaluation, RAG/LLM systems, and dependable data pipelines.

I’m a Data Scientist specializing in LLM evaluation, RAG systems, and applied ML across NLP, computer vision, and financial time-series problems. At Turing, I built systematic benchmarking frameworks that shaped model training cycles across 3+ versioning pipelines.

I design evaluation that improves both speed and quality—benchmarking accuracy, robustness, and instruction-following, standardizing error taxonomy, and enabling faster fine-tuning iterations. I also engineered a market-regime detection system on Nifty 50 data with strong predictive performance on 495 unseen 2024–2026 trading days.

I enjoy end-to-end problem solving, from dataset pipelines and quality standards to deployed, interactive systems. My projects include a real-time industry RAG analyzer that grounds responses in live sources and reduces stale-knowledge hallucinations through strict prompt engineering and vector retrieval.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Turing

Jun 2024 - Present (1 year 11 months)

Designed systematic LLM evaluation frameworks (accuracy, robustness, instruction-following) and used results to inform fine-tuning cycles across 3+ model versions, standardising error taxonomy to reduce evaluation turnaround time. Built large-scale dataset pipelines with feature selection, deduplication, and quality checks to maximize training signal and reduce label noise.

LLM Evaluation Prompt Engineering Model Fine Tuning Data Pipelines Data Quality Instruction Following Benchmarking Model Versioning

Business Analyst Intern

Whiteklay Technologies

May 2023 - Sep 2023 (4 months)

Built and enriched a banking analytics dataset using AI-assisted workflows, defining KPIs for core banking processes to improve data quality and traceability. Structured a data catalog for key business processes to enable consistent analytics across teams and reduce data discrepancies.

KPIs Data Quality Data Cataloging Data Governance Workflows Traceability Business Process Analysis

ML Engineer Intern

Credicxo Tech

May 2022 - Aug 2022 (3 months)

Built a CNN-GRU hybrid model with autoencoder-based feature extraction for bearing remaining useful life (RUL) prediction in a predictive maintenance workflow. Benchmarked transfer learning architectures for COVID-19 detection from chest X-rays and created an ensemble model that improved classification performance over individual baselines.

CNN GRU Models Transfer Learning Feature Extraction RUL Prediction Deep Learning

Data Analyst Intern

Sahu Technologies

May 2022 - Jun 2022 (1 month)

Developed automated web scraping pipelines to extract and structure business data using BeautifulSoup and Requests. Cleaned and prepared raw datasets to improve analysis reliability for internal reporting.

Web Scraping Python BeautifulSoup Data Cleaning Data Structuring Data & Analytics