Data Scientist · ML Engineer

I build production
machine learning systems.

I design model-serving infrastructure, RAG applications, and high-volume data pipelines that solve measurable operational problems.

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PythonPyTorchFastAPIAirflowDockerAWS

01 - ABOUT

About Me

I’m a data scientist and ML engineer focused on getting machine learning systems out of notebooks and into reliable production workflows.

I work across applied machine learning and platform engineering: designing model-serving stacks, building data and evaluation pipelines, and automating workflows that used to consume entire teams. The through-line is practical impact: faster decisions, lower operating cost, and systems people trust.

Currently, I’m a Data Scientist at Prime Healthcare, working at the intersection of healthcare operations, ML infrastructure, and agentic automation.

Annual waste reduction $1.6M

Forecasting 10K+ SKUs across 51 hospitals.

Pipeline speedup 48×

8 hours reduced to 10 minutes.

Analyst hours saved / month 200+

Hours returned every month.

Automation throughput 10×

With production coding agents, tool calling, and standardized evaluation.

02 - TECHNICAL STACK

Technical Stack

Languages & API Engineering

PythonC++Go (Golang)FastAPIFlaskREST APIs

Cloud & DevOps

AWSAWS LambdaAWS ECSAWS ALB AWS SageMakerAzureDockerPodman KubernetesGitHub ActionsCI/CD

AI, ML & Data

Machine LearningNLPLLMsRAG PyTorchTensorFlowKerasXGBoost Hugging FaceTransformersLangChainLangGraph OpenCVOCRComputer Vision

Databases & Messaging

SQLPostgreSQLMongoDBMySQL MSSQLNoSQLRedisRabbitMQApache Kafka

MLOps & Model Serving

vLLMMLflowAirflowMCP Model EvaluationCloud Infrastructure

Data & Retrieval

Knowledge GraphspgvectorPinecone FAISSVector DBsData Modeling

Tools & Practices

GitLinuxWindowsJira SeleniumSystem DesignExperimentation

03 - EXPERIENCE

Experience

Applied ML, data engineering, and infrastructure work across healthcare, security, computer vision, and research.

Building ML infrastructure and automation for healthcare operations at enterprise scale.

Built a guarded MCP server for production database tool-calling, reducing manual lookup by 70%+ across 10+ workflows.
Deployed vision-language invoice processing that reduced manual review by 80%+ and replaced an external vendor.
Architected a multi-model inference platform on clustered NVIDIA L40S servers with vLLM and parallel QLoRA variants.
Productionized Airflow-orchestrated EDI pipelines with exactly-once delivery and P99 latency under five seconds.
Led ERP data migration for an eight-hospital, $370M+ acquisition with zero data loss.

vLLMAirflowMCPRAGPythonPostgreSQL

Computer-vision research for road intelligence and autonomous-driving use cases.

Built road-sign detection pipelines and evaluated AutoML approaches on Google Cloud.
Benchmarked transfer-learning architectures including ResNet50, Xception, and InceptionResNetV2.

Computer VisionGCPTensorFlow

Risk intelligence for a university-wide vendor ecosystem.

Redesigned vendor-risk prediction for 28,000 vendors, reaching a 0.91 F1-score.
Reduced false positives by 15% through XGBoost deployment and A/B validation.
Automated alerts and Power BI reporting, saving more than 20 hours each week.

XGBoostPower BIPythonRisk Modeling

Efficient deep learning for chest X-ray diagnosis.

Developed a low-FLOP approach for COVID-19 and pneumonia detection.
Used U-Net encoder-decoder architectures to double training speed.
Deployed Micronet M3 with 99.3% accuracy and 99.31% F1-score.

Deep LearningU-NetMedical Imaging

Indoor positioning using wireless fingerprints and inertial signals.

Built k-NN and Random Forest positioning models with two-to-three meter precision.
Designed a real-time RSSI localization algorithm reaching 0.98 accuracy.

Random Forestk-NNLocalization

04 - EDUCATION

Education

LOS ANGELES, CA

University of Southern California

AUG 2021 - MAY 2023

Master of Science in Machine Learning and Data Science GPA: 3.81 / 4.0

RELEVANT COURSEWORK

Machine Learning, Deep Learning, Databases, Applied and Cloud Computing, Data Structures and Algorithms, Linear Algebra, Probability Theory, Digital Signal Processing

VELLORE, INDIA