Shivam Chaudhary

shivam.iitmandi@gmail.com GitHub LinkedIn

Summary

Senior Data Scientist with 6+ years applying scientific methods to high-stakes business problems, building production-grade ML/DL and end-to-end LLM/Agentic AI systems at scale. Hands-on across time-series forecasting, causal inference, recommendation, and large-scale data, with a product-oriented mindset and a habit of turning research into real-world impact.

Experience

Sr. Data Scientist — Aviso AIMay '25 – Present

Architected a multi-agent LLM system processing 100K+ deals daily across 15 enterprise clients, replacing rule-based logic with insight generation from CRM and engagement data, governed by evaluation and safety guardrails.
Replaced correlation-based explainability with a causal-inference backbone (Double Machine Learning, Causal Forests) to surface actionable recommendations — driving a ~12% increase in sales-rep engagement.
Built and scaled the LLM engineering function: defined the technical hiring bar and grew the team from 1 to 5 engineers for end-to-end development and production deployment.

Sr. Computer Vision Engineer — Bosch Global Software TechnologiesAug '22 – Apr '25

Published a research paper and filed a patent on enhancing foundation models (EVA-02), leveraging 90%+ unlabeled Bosch data to boost performance by ~5%; collaborated with Bosch Romania to further improve EVA by ~4.31% via cluster analysis and hypothesis testing on DINOv2 embeddings.
Built a Vision Assignment Marketplace, training SWin, DeiT, and DeTr with ~6.72% average performance deviation; designed a ConvNeXt segmentation pipeline on fisheye images (~57% F1).
Deployed an object detector and motion analyzer on a Jetson Nano edge test-bed at ~30 FPS; refactored legacy code for newer vision-transformer architectures, improving adaptability/efficiency by 14%.

Data Scientist II — HiLabs Inc.Oct '20 – Jul '22

Engineered a multi-million-dollar data pipeline moving anomalies from large-scale SQL/RDBMS sources to HBase and Solr for ticket-based remediation, improving Data Quality Index from ~78 to ~86; projected to prevent $200M+ in annual losses for a leading U.S. health insurer.
Deployed an enterprise-grade OCR solution (NLP + custom algorithms) on contracts after GAN-based image enhancement, generating $100K+ in business value.

Machine Learning Engineer Intern — GMO Research (Japan)Jan '20 – Mar '20

Forecast 6-hour survey response likelihood with time-aware Random Forests, Decision Trees, and DNNs; addressed class imbalance via SMOTE and custom metrics, achieving 91% efficacy on responsive marketing panels.

Skills

Languages & Libraries: Python, SQL, Scala, Pandas, NumPy, Scikit-Learn
Big Data & MLOps: Spark, Hadoop, HBase, Solr, AWS, Docker, Git, CI/CD, GPU/HPC
ML / DL / LLM: PyTorch, TensorFlow, Transformers, LangChain, LangGraph, RAG, Agentic AI, MCP
Models & Paradigms: Time-Series Forecasting, Recommendation, Causal Inference, Anomaly Detection, Computer Vision

Publications & Patents

Patent (co-authored): dimensionality-reduction techniques to detect and localize failure regions in segmentation outputs from foundation models, improving interpretability and reliability.
Research: a two-stage fine-tuning approach improving foundation-model segmentation performance by 5%+ mIoU using unlabeled data (semi-supervised learning).

Education

Indian Institute of Technology, MandiAug '16 – Jul '20

B.Tech in Mechanical Engineering, Minor in Intelligent Systems.