Available to hire
Hi there! I’m Vaishnav Kumar Chandha, a Data Scientist and AI/ML Engineer with 6+ years of experience turning data into actionable insights across financial services and healthcare. I enjoy building trusted, scalable solutions that balance accuracy with explainability and compliance.
In my work, I design and deploy models for credit risk, fraud detection, forecasting, and patient analytics using Python, SQL, and R on AWS, Azure, and GCP. I also automate data pipelines, explore generative AI and LLM-based workflows, and emphasize MLOps and SHAP-driven interpretability to enable auditable, data-driven decisions.
Skills
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Experience Level
Expert
Expert
Expert
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Expert
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Expert
Expert
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Intermediate
Language
English
Fluent
Work Experience
Data Scientist at Morgan Stanley USA
January 1, 2024 - PresentDesigned credit-scoring and delinquency-prediction models (Logistic Regression, XGBoost) with Risk, Quant, and Engineering teams, improving risk-forecast accuracy by 18% and strengthening portfolio resilience and loss-mitigation strategy. Built and deployed fraud-detection and anomaly-monitoring pipelines, reducing false positives by 22% and enhancing real-time transaction surveillance across institutional and retail portfolios. Engineered financial KPI forecasting models for capital-adequacy and liquidity planning, improving reporting precision by 25% and supporting strategic balance-sheet management. Architected and automated AWS data pipelines (Glue, Redshift, Lambda) processing 2M+ daily records, cutting data latency by 40% and ensuring timely, accurate ingestion for model training and reporting. Implemented Generative AI and LLM-powered RAG pipelines to automate credit-policy summarization, compliance alerting, and risk-report generation, decreasing manual review time by 35%. Part
AI/ML Engineer at Fortis Medical India
January 1, 2018 - July 1, 2022Developed patient-demand and resource-utilization forecasting models (Prophet, ARIMA, LSTM), improving admission/discharge forecast accuracy by 25% (RMSE) and reducing bed and staff over-allocation costs by 15% across departments. Built patient-churn and risk-prediction models (XGBoost, Random Forest, K-Means), increasing patient retention by 30%, improving follow-up adherence by 20%, and enabling personalized care-outreach programs. Led A/B testing and statistical experimentation with clinical, telemedicine, and marketing teams to evaluate dynamic appointment pricing and outreach campaigns, raising patient conversion and engagement by 6%. Engineered real-time anomaly-detection pipelines (Isolation Forest, streaming analytics) to flag abnormal patient-inflow patterns, reducing ER bottlenecks and minimizing service downtime. Deployed scalable Azure data pipelines integrating EHR, patient-feedback, and billing data for unified analytics and HIPAA-compliant AI model deployment. Built inte
Education
M.S. at Saint Leo University
January 11, 2030 - May 1, 2024Qualifications
Microsoft Certified: Azure Data Engineer Associate (DP-203)
January 11, 2030 - July 2, 2026Industry Experience
Financial Services, Healthcare
Skills
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Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
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