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Senior AI/ML Engineer and Data Scientist with 9+ years of experience delivering production AI solutions across healthcare, finance, and technology. Expert in agentic AI systems, RAG frameworks, LLM evaluation, and scalable MLOps pipelines on AWS, GCP, and Azure, with measurable cost and revenue impact. Leads cross-functional teams end-to-end across deep learning/NLP and predictive analytics, specializing in model monitoring, bias/hallucination controls, and secure/privacy-first deployment. Proven track record includes improving retrieval accuracy, reducing deployment cycles, and improving business outcomes through data-driven experimentation and ML observability.…Senior AI/ML Engineer and Data Scientist with 9+ years of experience delivering production AI solutions across healthcare, finance, and technology. Expert in agentic AI systems, RAG frameworks, LLM evaluation, and scalable MLOps pipelines on AWS, GCP, and Azure, with measurable cost and revenue impact. Leads cross-functional teams end-to-end across deep learning/NLP and predictive analytics, specializing in model monitoring, bias/hallucination controls, and secure/privacy-first deployment. Proven track record includes improving retrieval accuracy, reducing deployment cycles, and improving business outcomes through data-driven experimentation and ML observability.

Sharath Chandra

AI Engineer, Data Scientist, Developer, +2

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Senior AI/ML Engineer and Data Scientist with 9+ years of experience delivering production AI solutions across healthcare, finance, and technology. Expert in agentic AI systems, RAG frameworks, LLM evaluation, and scalable MLOps pipelines on AWS, GCP, and Azure, with measurable cost and revenue impact. Leads cross-functional teams end-to-end across deep learning/NLP and predictive analytics, specializing in model monitoring, bias/hallucination controls, and secure/privacy-first deployment. Proven track record includes improving retrieval accuracy, reducing deployment cycles, and improving business outcomes through data-driven experimentation and ML observability.…Senior AI/ML Engineer and Data Scientist with 9+ years of experience delivering production AI solutions across healthcare, finance, and technology. Expert in agentic AI systems, RAG frameworks, LLM evaluation, and scalable MLOps pipelines on AWS, GCP, and Azure, with measurable cost and revenue impact. Leads cross-functional teams end-to-end across deep learning/NLP and predictive analytics, specializing in model monitoring, bias/hallucination controls, and secure/privacy-first deployment. Proven track record includes improving retrieval accuracy, reducing deployment cycles, and improving business outcomes through data-driven experimentation and ML observability.

Available to hire

Senior AI/ML Engineer and Data Scientist with 9+ years of experience delivering production AI solutions across healthcare, finance, and technology. Expert in agentic AI systems, RAG frameworks, LLM evaluation, and scalable MLOps pipelines on AWS, GCP, and Azure, with measurable cost and revenue impact.

Leads cross-functional teams end-to-end across deep learning/NLP and predictive analytics, specializing in model monitoring, bias/hallucination controls, and secure/privacy-first deployment. Proven track record includes improving retrieval accuracy, reducing deployment cycles, and improving business outcomes through data-driven experimentation and ML observability.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

Senior AI/ML Engineer at Silicon Valley Bank (SVB)

October 1, 2025 - Present

Architected agentic AI orchestration for venture capital due diligence using Claude and LangGraph, reducing manual analysis time by 65%. Built a RAG-based financial advisor integrated with Snowflake Cortex and Pinecone, improving knowledge retrieval accuracy by 40% and cutting support ticket volume by 12%. Engineered real-time liquidity risk monitoring using SageMaker and Kafka with 25% faster response times. Developed fraud detection using GNNs to identify $4.2M previously undetected suspicious patterns. Led migration of on-prem ML workloads to AWS and Snowflake, delivering $1.2M (30%) annual reduction in cloud infrastructure and compute costs. Implemented automated LLM evaluation (LLM-as-a-judge) for hallucination and bias monitoring with 99.8% compliance to internal AI safety standards. Supervised CI/CD pipeline development for LLM Ops, reducing deployment cycle time from three weeks to four days.

Senior Data Scientist at CVS Health

August 1, 2023 - September 30, 2025

Developed predictive healthcare outcomes using transformer models, improving patient adherence predictions by 24% across 10M pharmacy records. Built a scalable NLP pipeline for clinical note summarization, saving clinicians ~1.5 hours/day and reducing administrative overhead by $2M annually. Engineered real-time supply chain optimization reducing pharmaceutical waste by 15% via improved regional demand forecasting. Designed an RL framework for personalized wellness recommendations, increasing engagement in the CVS MyChart app by 35%. Established MLOps foundation using MLflow and GCP Vertex AI, cutting model redeployment time by 45% and enabling seamless version control. Integrated predictive risk scores into physician workflows, reducing ER readmission rates by 12% for high-risk cohorts.

Data Scientist at Vanguard

May 1, 2022 - July 31, 2023

Architected a deep learning customer churn model with LSTM networks to retain $3.5M in assets under management in the first year. Developed k-means clustering for high-net-worth segmentation, improving targeted marketing ROI by 22%. Built distributed data processing with Hadoop and Spark ingesting 500GB+ of daily market data, reducing analytics report latency by 30%. Engineered a time-series forecasting model for mutual fund performance improving MAPE by 15% over historical benchmarks. Partnered with quantitative research to support backtesting and trading strategy validation leading to a 5% increase in seasonality yields. Implemented automated feature engineering pipelines, reducing data preparation time for new model development by 40%.

Data Scientist at Verizon

February 1, 2021 - April 30, 2022

Built a sales forecasting model using gradient boosting (XGBoost) improving quarterly revenue prediction accuracy by 12% to support budget allocation. Created executive Tableau dashboards automating weekly reporting and saving 15 manual analytics hours per week. Analyzed large-scale telecommunications network data to identify churn indicators, enabling a targeted retention campaign saving $1.2M in annual revenue. Automated data cleaning and ingestion scripts with Python and SQL, reducing ETL time by 25%. Engineered SQL-based ETL pipelines processing 100GB of unstructured call logs daily to ensure data availability for real-time business intelligence. Designed and executed A/B tests for website UI elements driving a 7% lift in mobile plan conversions over six months. Optimized SQL queries and data indexing improving performance for large-scale analytical joins by 30%.

Junior Data Analyst at CMC Limited

June 1, 2017 - October 1, 2020

Analyzed regional sales trends using Excel and SQL to optimize inventory stock levels, reducing inventory carrying costs by 10% across five warehouses. Developed automated management reports saving 10 hours/week of manual data entry across three major departments. Crafted complex SQL queries extracting market performance insights from legacy databases, improving report turnaround time by 15%. Assisted with A/B testing for promotional email campaigns leading to a 7% increase in customer engagement and open rates. Built regression models in Excel forecasting monthly demand achieving 90% accuracy for stable product lines. Improved data integrity by identifying historical data entry inconsistencies, increasing sales database integrity by 20%.