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I am a Data Scientist and AI/ML Engineer with 4+ years of experience applying machine learning, predictive analytics, and Generative AI to high-stakes problems in financial services and healthcare.\n\nIn my work, I build credit-risk, fraud-detection, forecasting, and patient-analytics models in Python, SQL, and R on AWS, Azure, and GCP, and I engineer automated, production-grade data pipelines. I specialize in LLM and RAG architectures, statistical modeling, experimentation, and explainable AI (SHAP) to drive auditable, data-driven decisions and regulatory compliance, translating complex analysis into measurable business impact across large enterprise environments.…I am a Data Scientist and AI/ML Engineer with 4+ years of experience applying machine learning, predictive analytics, and Generative AI to high-stakes problems in financial services and healthcare.\n\nIn my work, I build credit-risk, fraud-detection, forecasting, and patient-analytics models in Python, SQL, and R on AWS, Azure, and GCP, and I engineer automated, production-grade data pipelines. I specialize in LLM and RAG architectures, statistical modeling, experimentation, and explainable AI (SHAP) to drive auditable, data-driven decisions and regulatory compliance, translating complex analysis into measurable business impact across large enterprise environments.

Seelam Krushender Reddy

Data Scientist, AI Engineer, AI Developer, +2

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I am a Data Scientist and AI/ML Engineer with 4+ years of experience applying machine learning, predictive analytics, and Generative AI to high-stakes problems in financial services and healthcare.\n\nIn my work, I build credit-risk, fraud-detection, forecasting, and patient-analytics models in Python, SQL, and R on AWS, Azure, and GCP, and I engineer automated, production-grade data pipelines. I specialize in LLM and RAG architectures, statistical modeling, experimentation, and explainable AI (SHAP) to drive auditable, data-driven decisions and regulatory compliance, translating complex analysis into measurable business impact across large enterprise environments.…I am a Data Scientist and AI/ML Engineer with 4+ years of experience applying machine learning, predictive analytics, and Generative AI to high-stakes problems in financial services and healthcare.\n\nIn my work, I build credit-risk, fraud-detection, forecasting, and patient-analytics models in Python, SQL, and R on AWS, Azure, and GCP, and I engineer automated, production-grade data pipelines. I specialize in LLM and RAG architectures, statistical modeling, experimentation, and explainable AI (SHAP) to drive auditable, data-driven decisions and regulatory compliance, translating complex analysis into measurable business impact across large enterprise environments.

Available to hire

I am a Data Scientist and AI/ML Engineer with 4+ years of experience applying machine learning, predictive analytics, and Generative AI to high-stakes problems in financial services and healthcare.\n\nIn my work, I build credit-risk, fraud-detection, forecasting, and patient-analytics models in Python, SQL, and R on AWS, Azure, and GCP, and I engineer automated, production-grade data pipelines. I specialize in LLM and RAG architectures, statistical modeling, experimentation, and explainable AI (SHAP) to drive auditable, data-driven decisions and regulatory compliance, translating complex analysis into measurable business impact across large enterprise environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Data Scientist at S&P Global

January 1, 2025 - Present

Designed credit-scoring and delinquency-prediction models with Logistic Regression, XGBoost, and Python, improving risk-forecast accuracy by 18% and strengthening loss-mitigation strategies. Developed and deployed fraud-detection and anomaly-monitoring pipelines, reducing false positives by 22% and enhancing real-time transaction surveillance. Engineered KPI forecasting models for capital-adequacy and liquidity planning, improving reporting precision by 25%. Built and automated AWS data pipelines (Glue, Redshift, Lambda) processing 2M+ daily records, reducing data latency by 40%. Implemented Generative AI and LLM-powered RAG pipelines to automate credit-policy summarization, compliance alerting, and risk reporting, cutting manual review time by 35%. Produced explainable AI insights with SHAP, enabling auditable model interpretability for risk, compliance, and governance teams.

AI/ML Engineer at KPIT

February 1, 2021 - July 1, 2024

Built patient-demand and resource-utilization forecasting models with Prophet, ARIMA, and LSTM, improving admission forecast accuracy by 25% (RMSE) and cutting bed/staff over-allocation costs by 15%. Developed patient churn and risk-prediction models using XGBoost, Random Forest, and K-Means, improving patient retention by 30% and follow-up adherence by 20% for personalized care outreach. Led A/B testing and statistical experimentation with clinical, telemedicine, and marketing teams to evaluate dynamic appointment pricing and outreach, lifting patient conversion by 6%. Engineered real-time anomaly-detection pipelines with Isolation Forest and streaming analytics, enabling early detection of abnormal patient-inflow patterns and reducing ER bottlenecks. Designed and deployed scalable Azure data pipelines integrating EHR, patient-feedback, and billing data for secure, unified analytics in compliance with HIPAA standards.