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Sanket Bhujbal

@sanketbhujbal

Data Scientist/ML/AI Engineer with 3 years of experience building end-to-end machine learning systems, data pipelines, and AI-powered applications.

United States

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What I'm looking for

I’m looking for a role where I can solve real business problems using data, machine learning, and software engineering. I enjoy building end-to-end solutions, collaborating with cross-functional teams, and continuously learning new technologies. Most importantly, I want to work in an environment that values ownership, curiosity, and delivering measurable impact.

Data Scientist/ML/AI Engineer with 3 years of experience building end-to-end machine learning systems, data pipelines, and AI-powered applications across retail, nonprofit, and enterprise consulting domains. Holds a Master's in Computer Science from Virginia Tech, USA. Hands-on experience with full ML lifecycle: from data ingestion and feature engineering to model deployment and monitoring. Recent work spans LLM-based systems (RAG pipelines, prompt engineering, LLM evaluation), recommender systems, NLP, causal inference, experimentation and forecasting. Proven ability to deliver measurable impact: boosted campaign conversions by ~20% via donor segmentation, achieved AUC-ROC of 0.85 on a collaborative filtering system, and reduced reporting errors by ~15%. Comfortable working across the data stack from ETL pipelines and vector databases to REST APIs and production dashboards. Actively seeking roles in Data Science, ML Engineering, or AI/LLM Engineering.

Experience

Work history, roles, and key accomplishments

AI Engineer

Executive Software Guild

Feb 2026 - May 2026 (3 months)

Built an internal RAG-based knowledge base used by 200 consultants to retrieve historical project data and SAP implementation
guidelines, reducing time spent searching legacy documentation
Improved LLM output quality (GPT-4, Claude) by refining prompts to enforce context grounding and structured response templates.
Average accuracy rose from 3.9/5 to 4.5/5 and completeness from 3.7/5 to 4.4/5

Data Analyst

bright mind enrichment

Mar 2025 - Feb 2026 (11 months)

Built an RFM-based donor segmentation model across 6-8k historical records, prioritizing outreach toward high-intent segments (loyal, recent high-value, at-risk) instead of uniform campaigns. Conversion improved from about 5% to 6%, a ~20% relative lift, while cutting outreach to low-response donors
• Audited and standardized legacy donor data spanning fundraising, finance, and alumni relations.

Data Analyst

Comsense Technologies

Jun 2021 - Nov 2022 (1 year 5 months)

Developed a collaborative filtering recommender system for a retail client using Implicit, achieving AUC-ROC of 0.85 on temporal test data
Engineered a data pipeline transforming raw transaction logs into Compressed Sparse Row matrices
Optimized model performance by tuning latent factors and regularization parameters, lifting top-N recommendation relevance by ~10% over popularity-based baselines