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I am a Data Scientist, Machine Learning Engineer, and AI Practitioner with 7 years of experience delivering AI/ML solutions at scale across telecom, healthcare, banking, and finance industries. I bridge business goals with technical innovation and excel in cloud-native, end-to-end ML lifecycles from data preparation to production deployment and monitoring. I enjoy leading AI initiatives, mentoring junior analysts, and building scalable ML systems, NLP pipelines, and GenAI-enabled solutions. I thrive on transforming complex data into actionable insights, implementing responsible AI, and enabling data-driven decisions across cross-functional teams.…I am a Data Scientist, Machine Learning Engineer, and AI Practitioner with 7 years of experience delivering AI/ML solutions at scale across telecom, healthcare, banking, and finance industries. I bridge business goals with technical innovation and excel in cloud-native, end-to-end ML lifecycles from data preparation to production deployment and monitoring. I enjoy leading AI initiatives, mentoring junior analysts, and building scalable ML systems, NLP pipelines, and GenAI-enabled solutions. I thrive on transforming complex data into actionable insights, implementing responsible AI, and enabling data-driven decisions across cross-functional teams.

Lakshmi Mupparaju

Data Scientist, AI Engineer, AI Developer, +6

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I am a Data Scientist, Machine Learning Engineer, and AI Practitioner with 7 years of experience delivering AI/ML solutions at scale across telecom, healthcare, banking, and finance industries. I bridge business goals with technical innovation and excel in cloud-native, end-to-end ML lifecycles from data preparation to production deployment and monitoring. I enjoy leading AI initiatives, mentoring junior analysts, and building scalable ML systems, NLP pipelines, and GenAI-enabled solutions. I thrive on transforming complex data into actionable insights, implementing responsible AI, and enabling data-driven decisions across cross-functional teams.…I am a Data Scientist, Machine Learning Engineer, and AI Practitioner with 7 years of experience delivering AI/ML solutions at scale across telecom, healthcare, banking, and finance industries. I bridge business goals with technical innovation and excel in cloud-native, end-to-end ML lifecycles from data preparation to production deployment and monitoring. I enjoy leading AI initiatives, mentoring junior analysts, and building scalable ML systems, NLP pipelines, and GenAI-enabled solutions. I thrive on transforming complex data into actionable insights, implementing responsible AI, and enabling data-driven decisions across cross-functional teams.

Available to hire

I am a Data Scientist, Machine Learning Engineer, and AI Practitioner with 7 years of experience delivering AI/ML solutions at scale across telecom, healthcare, banking, and finance industries. I bridge business goals with technical innovation and excel in cloud-native, end-to-end ML lifecycles from data preparation to production deployment and monitoring.

I enjoy leading AI initiatives, mentoring junior analysts, and building scalable ML systems, NLP pipelines, and GenAI-enabled solutions. I thrive on transforming complex data into actionable insights, implementing responsible AI, and enabling data-driven decisions across cross-functional teams.

Skills

Experience Level

Expert

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Expert

Language

English

Fluent

Work Experience

Senior Data Scientist / ML Engineer at T-Mobile

March 1, 2024 - November 5, 2025

Designed and deployed AI-driven chatbots and LLM-powered assistants; implemented Retrieval-Augmented Generation (RAG) with Pinecone for telecom support; improved customer query accuracy by 40%. Fine-tuned LLaMA and Mistral on telecom data to reduce hallucinations and cut error rate by 25%. Built real-time inference APIs with FastAPI & AWS Lambda handling 100K+ queries per day with latency <200 ms. Implemented OCR+NLP pipelines for invoice/document parsing, saving 200+ hours per month. Created vector DB pipelines (FAISS, Pinecone, Chroma) for enhanced contextual retrieval. Migrated ML infrastructure to GCP (Vertex AI, BigQuery, GKE) reducing compute costs by 20%. Implemented MLOps with Kubeflow + MLflow and integrated RAG with knowledge-base retrieval. Mentored junior data scientists and collaborated with AI governance to onboard GenAI use cases.

Data Scientist at The Cigna Group

February 1, 2024 - February 1, 2024

Developed predictive ML models (Logistic Regression, Bayesian Regression, XGBoost) to optimize patient outcomes and reduce healthcare costs. Built NER pipelines with spaCy + AWS Comprehend for EHR entity extraction. Designed LLM-based summarization tools for clinical trial reports, reducing manual review time by 50%. Automated data pipelines with GCP Dataflow + PySpark, cutting ETL processing by 35%. Deployed multi-model serving pipelines on Vertex AI with automated rollback and access control. Migrated workloads to AWS SageMaker + Azure ML to improve latency and scalability. Built recommendation systems for personalized healthcare plans and implemented Kubeflow pipelines for MLOps automation. Reduced cloud costs via model compression and optimization. Collaborated with governance bodies to ensure HIPAA/regulatory alignment; on-boarded models into enterprise workflows.

Data Scientist at Innomax IT Solutions

July 1, 2022 - July 1, 2022

Built fraud detection models (Random Forest, Logistic Regression, Neural Nets) reducing fraud losses by 22%. Designed anomaly detection systems on credit card transactions, cutting false positives by 18%. Created risk scoring models with ensemble methods and built real-time monitoring pipelines using Kafka + GCP Pub/Sub. Automated ETL workflows in SQL & Python; performed EDA + feature engineering across billions of transaction records. Implemented RCNNs for time-series analysis; deployed real-time fraud pipelines on AWS EMR + Glue + Redshift; integrated S3 + Lambda for scalable workflows. Built dashboards in Tableau & Power BI; optimized ML models with hyperparameter tuning; introduced Vertex AI-like pipelines for automated deployment. Collaborated with risk/compliance teams to ensure regulatory alignment.

Senior Data Scientist / ML Engineer at T-Mobile

March 1, 2024 - November 18, 2025

Designed and deployed AI-driven chatbots, LLM-powered assistants, and predictive ML systems to enhance customer support and telecom operations. Implemented RAG-based AI chatbot with Pinecone; fine-tuned LLaMA and Mistral to reduce hallucinations; built real-time inference APIs (FastAPI & AWS Lambda); designed ETL pipelines (AWS EMR + Glue); OCR/NLP for invoicing; LangChain workflows; governance, vector stores, and retrieval-based retrieval; multi-agent GenAI workflows; and monitoring dashboards.

Data Scientist at The Cigna Group

January 1, 2023 - February 29, 2024

Developed predictive ML models (Logistic Regression, Bayesian Regression, XGBoost) to optimize patient outcomes and reduce healthcare costs by 18%. Built NER pipelines with spaCy + AWS Comprehend to extract clinical entities from EHRs. Implemented LLM-based summarization tools for clinical trial reports, cutting manual review time by 50%. Automated data pipelines with GCP Dataflow & PySpark, accelerating ETL by 35%. Designed Vertex AI pipelines for automated model retraining with robust access control. Deployed models on AWS SageMaker and Azure ML, reducing inference latency by 40%. Collaborated with governance bodies to ensure HIPAA compliance, Disaster Recovery, and onboarding into enterprise workflows. Created recommendation systems for personalized healthcare plans and deployed disaster recovery strategies for ML endpoints. Implemented Kubeflow pipelines for MLOps automation and introduced explainable AI (LIME, SHAP) for clinical decision support.

Data Scientist at Innomax IT Solutions

June 1, 2018 - July 1, 2022

Built fraud detection models (Random Forest, Logistic Regression, Neural Nets) reducing fraud losses by 22%. Developed time-series forecasting with ARIMA, RNN, LSTM and anomaly detection for real-time monitoring. Created real-time fraud alerting API consumed by banking apps and built risk scoring models with ensemble methods. Implemented ETL pipelines with SQL & Python; conducted EDA across billions of transaction records. Built real-time fraud pipelines using Kafka + GCP Pub/Sub; designed graph-based ML models for fraud ring detection; established data lineage for compliance. Developed dashboards in Tableau & Power BI; reduced pipeline runtimes by 30% via PySpark and SQL optimization. Implemented OCR on financial documents; deployed with Vertex AI and AWS for scalable ML deployments.