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I am Rama Bala Muppalla, a Senior ML Engineer with 9+ years of AI/ML experience delivering end-to-end solutions across healthcare, banking, fintech, and retail. I specialize in building, deploying, and operationalizing models in regulated environments, managing the full lifecycle from data ingestion to monitoring, using Python, PySpark, TensorFlow, PyTorch, and cloud-native pipelines across AWS, Azure, and GCP. I’ve designed GenAI and Retrieval-Augmented Generation (RAG) frameworks with LangChain, vector databases, embeddings search, and LLM orchestration to power document AI, clinical summarization, search assistants, and regulatory automation. I also build agent-based GenAI systems for multi-step reasoning and task orchestration, with robust monitoring, governance, and explainability to ensure reliable behavior in regulated environments. I enjoy collaborating with clinicians, risk analysts, data engineers, and compliance teams to translate business needs into auditable ML solutions.…I am Rama Bala Muppalla, a Senior ML Engineer with 9+ years of AI/ML experience delivering end-to-end solutions across healthcare, banking, fintech, and retail. I specialize in building, deploying, and operationalizing models in regulated environments, managing the full lifecycle from data ingestion to monitoring, using Python, PySpark, TensorFlow, PyTorch, and cloud-native pipelines across AWS, Azure, and GCP. I’ve designed GenAI and Retrieval-Augmented Generation (RAG) frameworks with LangChain, vector databases, embeddings search, and LLM orchestration to power document AI, clinical summarization, search assistants, and regulatory automation. I also build agent-based GenAI systems for multi-step reasoning and task orchestration, with robust monitoring, governance, and explainability to ensure reliable behavior in regulated environments. I enjoy collaborating with clinicians, risk analysts, data engineers, and compliance teams to translate business needs into auditable ML solutions.

Rama Bala Muppalla

Data Scientist, AI Engineer, Cloud Developer, +4

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I am Rama Bala Muppalla, a Senior ML Engineer with 9+ years of AI/ML experience delivering end-to-end solutions across healthcare, banking, fintech, and retail. I specialize in building, deploying, and operationalizing models in regulated environments, managing the full lifecycle from data ingestion to monitoring, using Python, PySpark, TensorFlow, PyTorch, and cloud-native pipelines across AWS, Azure, and GCP. I’ve designed GenAI and Retrieval-Augmented Generation (RAG) frameworks with LangChain, vector databases, embeddings search, and LLM orchestration to power document AI, clinical summarization, search assistants, and regulatory automation. I also build agent-based GenAI systems for multi-step reasoning and task orchestration, with robust monitoring, governance, and explainability to ensure reliable behavior in regulated environments. I enjoy collaborating with clinicians, risk analysts, data engineers, and compliance teams to translate business needs into auditable ML solutions.…I am Rama Bala Muppalla, a Senior ML Engineer with 9+ years of AI/ML experience delivering end-to-end solutions across healthcare, banking, fintech, and retail. I specialize in building, deploying, and operationalizing models in regulated environments, managing the full lifecycle from data ingestion to monitoring, using Python, PySpark, TensorFlow, PyTorch, and cloud-native pipelines across AWS, Azure, and GCP. I’ve designed GenAI and Retrieval-Augmented Generation (RAG) frameworks with LangChain, vector databases, embeddings search, and LLM orchestration to power document AI, clinical summarization, search assistants, and regulatory automation. I also build agent-based GenAI systems for multi-step reasoning and task orchestration, with robust monitoring, governance, and explainability to ensure reliable behavior in regulated environments. I enjoy collaborating with clinicians, risk analysts, data engineers, and compliance teams to translate business needs into auditable ML solutions.

Available to hire

I am Rama Bala Muppalla, a Senior ML Engineer with 9+ years of AI/ML experience delivering end-to-end solutions across healthcare, banking, fintech, and retail. I specialize in building, deploying, and operationalizing models in regulated environments, managing the full lifecycle from data ingestion to monitoring, using Python, PySpark, TensorFlow, PyTorch, and cloud-native pipelines across AWS, Azure, and GCP.

I’ve designed GenAI and Retrieval-Augmented Generation (RAG) frameworks with LangChain, vector databases, embeddings search, and LLM orchestration to power document AI, clinical summarization, search assistants, and regulatory automation. I also build agent-based GenAI systems for multi-step reasoning and task orchestration, with robust monitoring, governance, and explainability to ensure reliable behavior in regulated environments. I enjoy collaborating with clinicians, risk analysts, data engineers, and compliance teams to translate business needs into auditable ML solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior Data Scientist / Machine Learning Engineer at Spencer Health

January 1, 2025 - Present

Collaborated with clinical, operational, and business stakeholders to understand healthcare objectives, define success metrics, and translate care-utilization and risk problems into well-scoped ML use cases. Ingested EHR, claims, and patient monitoring data from enterprise platforms, supporting structured and unstructured data sources in batch and near-real-time pipelines. Built data ingestion/transformation pipelines with Delta Lake on Azure Databricks, with data-quality checks and schema enforcement. Performed EDA and feature engineering with PySpark/SQL to create analytics-ready features for modeling. Engineered feature pipelines ensuring consistency between training workflows and real-time inference services. Developed patient risk-scoring and care-utilization forecasting models using time-series, ensemble, and statistical techniques. Implemented end-to-end NLP pipelines using Transformer-based models to extract structured insights from unstructured clinical notes. Trained, tuned,

Senior Data Scientist / Machine Learning Engineer at Deutsche Bank

July 1, 2023 - December 1, 2024

Developed risk, fraud detection, AML, and forecasting models to support trading, treasury, and regulatory reporting. Ingested large-scale trading, KYC, and transactional data; engineered scalable PySpark/SQL pipelines and loaded curated data into Snowflake and Google BigQuery. Implemented data-quality validation, lineage tracking, and compliance controls. Performed EDA and created reusable feature pipelines for multiple analytics teams. Built models for risk prediction, AML detection, and anomaly detection using gradient boosting and deep learning. Created time-series forecasting pipelines for liquidity, exposure, and KPIs (ARIMA, Prophet, LSTM). Designed event-detection models on high-frequency time-series data. Implemented data sampling and class-imbalance handling to improve detection performance. Conducted scenario-based stress testing and integrated ML models into Kafka-based streaming for near real-time scoring. Automated training, retraining, inference, and monitoring with Airfl

Senior Data Scientist at Broadridge

January 1, 2020 - June 1, 2023

Led intelligent document-processing initiatives, including automated classification, information extraction, and summarization of regulatory filings and financial documents. Implemented OCR (Tesseract) with Transformer-based models for structured data extraction. Built scalable ETL/ML pipelines on AWS (S3, SageMaker, Redshift) to support batch and near-real-time processing. Developed revenue, transaction-volume, and operational forecasting models; deployed ML inference services with FastAPI; migrated legacy analytics components to containerized microservices. Established CI/CD pipelines (Jenkins, GitHub) and built model monitoring dashboards for performance and data quality. Created model governance artifacts (validation reports, documentation, model cards) to support audits and regulatory reviews. Collaborated with business and compliance teams to validate KPIs and ensure alignment with regulatory needs.

Data Scientist at Iota Technologies Ltd

July 1, 2017 - August 1, 2019

Delivered ML-driven analytics solutions for retail and telecom, focusing on churn prediction, customer segmentation, and operational insights. Built data ingestion and preprocessing workflows for large-scale datasets; developed Tableau dashboards for stakeholder communication. Engineered statistical and behavioral features to boost model performance and conducted A/B testing to validate strategies. Deployed batch ML models on AWS EC2 with automated inference routines and documented reproducible workflows.

Junior Data Scientist at Aufait Technologies Pvt. Ltd.

April 1, 2016 - June 1, 2017

Supported enterprise clients transitioning to data-driven analytics; built dashboards and automated reports to replace manual processes. Developed early-stage ML prototypes for classification and clustering; prepared datasets and validated outputs. Deployed small-scale ML services on Azure, implemented data-quality checks, and documented workflows for reproducibility. Collaborated with senior data scientists to integrate ML outputs into applications and ensured security/compliance.

Data Scientist at Aufait Technologies Pvt. Ltd.

April 1, 2016 - June 1, 2017

Supported enterprise clients transitioning from manual reporting to data-driven analytics by building dashboards and automated reports, prototyping ML prototypes for classification and clustering, and delivering actionable operational insights. Created SQL data transformations for analytics datasets, built Tableau dashboards, and deployed small-scale ML services on Azure. Tuned baseline models, documented performance results, and ensured data security and access control per enterprise standards. Collaborated with senior data scientists to ensure reproducibility and maintainability of analytics workflows.

Senior ML Engineer (AI Engineer) at Spencer Health

January 1, 2025 - Present

Led end-to-end ML initiatives for healthcare operations, including automated clinical summarization, coding assistance, claims intelligence, risk scoring, and care-management automation. Built NLP pipelines to process large volumes of unstructured clinical data, deployed inference services as REST APIs on Kubernetes, and implemented monitoring, retraining triggers, and HIPAA-compliant data handling to ensure reliability in regulated environments.

Senior ML Engineer / AI Engineer at Deutsche Bank

July 1, 2023 - December 31, 2024

Developed ML and NLP systems for AML risk scoring, transaction anomaly detection, and regulatory reporting automation. Built scalable Spark-based pipelines processing millions of transactions daily, deployed REST inference services, and ensured explainability and audit readiness in a highly regulated BFSI environment. Led end-to-end lifecycle: data prep, feature engineering, model training, validation, and production deployment.

Senior ML Engineer at Broadridge

January 1, 2020 - June 30, 2023

Built ML systems to support trade-processing automation, financial document intelligence, anomaly detection, and predictive analytics for high-volume trading platforms. Developed NLP classifiers, OCR workflows, and Spark-based ETL pipelines; exposed predictions via REST APIs; implemented CI/CD and monitoring to ensure reliability in production; collaborated with compliance and quants for auditability.

ML Engineer / Data Scientist at Iota Technologies Ltd

July 1, 2017 - August 31, 2019

Delivered ML and NLP solutions for retail analytics, pricing automation, demand forecasting, and customer behavior analysis. Built forecasting and pricing models; developed sentiment analysis and topic modeling pipelines; created Spark-based ETL pipelines.

Data Analyst / Junior ML Engineer at Aufait Technologies Pvt. Ltd.

April 1, 2016 - June 30, 2017

Supported early ML initiatives by preparing datasets, building baseline models, automating reports and dashboards, and collaborating with senior data scientists to improve data quality and reproducibility.