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Hi, I'm Meghana Chirumamilla, a Senior AI Data Scientist with over 7 years of experience crafting and deploying end-to-end AI and machine learning pipelines in cloud environments like Azure and AWS. I enjoy building scalable, production-grade models, especially working on generative AI and LLM applications, and integrating vector search systems to empower enterprise knowledge systems. I thrive on collaborating across teams to bring AI solutions to life, whether it’s automating business workflows, enhancing document classification, or developing real-time fraud detection models. I'm passionate about mentoring teammates and sharing knowledge on MLOps best practices and model interpretability to create transparent and impactful AI applications.…Hi, I'm Meghana Chirumamilla, a Senior AI Data Scientist with over 7 years of experience crafting and deploying end-to-end AI and machine learning pipelines in cloud environments like Azure and AWS. I enjoy building scalable, production-grade models, especially working on generative AI and LLM applications, and integrating vector search systems to empower enterprise knowledge systems. I thrive on collaborating across teams to bring AI solutions to life, whether it’s automating business workflows, enhancing document classification, or developing real-time fraud detection models. I'm passionate about mentoring teammates and sharing knowledge on MLOps best practices and model interpretability to create transparent and impactful AI applications.

Meghana Chirumamilla

Data Scientist, AI Engineer, AI Prompt Engineer, +2

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Hi, I'm Meghana Chirumamilla, a Senior AI Data Scientist with over 7 years of experience crafting and deploying end-to-end AI and machine learning pipelines in cloud environments like Azure and AWS. I enjoy building scalable, production-grade models, especially working on generative AI and LLM applications, and integrating vector search systems to empower enterprise knowledge systems. I thrive on collaborating across teams to bring AI solutions to life, whether it’s automating business workflows, enhancing document classification, or developing real-time fraud detection models. I'm passionate about mentoring teammates and sharing knowledge on MLOps best practices and model interpretability to create transparent and impactful AI applications.…Hi, I'm Meghana Chirumamilla, a Senior AI Data Scientist with over 7 years of experience crafting and deploying end-to-end AI and machine learning pipelines in cloud environments like Azure and AWS. I enjoy building scalable, production-grade models, especially working on generative AI and LLM applications, and integrating vector search systems to empower enterprise knowledge systems. I thrive on collaborating across teams to bring AI solutions to life, whether it’s automating business workflows, enhancing document classification, or developing real-time fraud detection models. I'm passionate about mentoring teammates and sharing knowledge on MLOps best practices and model interpretability to create transparent and impactful AI applications.

Available to hire

Hi, I’m Meghana Chirumamilla, a Senior AI Data Scientist with over 7 years of experience crafting and deploying end-to-end AI and machine learning pipelines in cloud environments like Azure and AWS. I enjoy building scalable, production-grade models, especially working on generative AI and LLM applications, and integrating vector search systems to empower enterprise knowledge systems.

I thrive on collaborating across teams to bring AI solutions to life, whether it’s automating business workflows, enhancing document classification, or developing real-time fraud detection models. I’m passionate about mentoring teammates and sharing knowledge on MLOps best practices and model interpretability to create transparent and impactful AI applications.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Hindi

Advanced

Work Experience

Senior AI Data Scientist at Appian

May 1, 2024 - Present

Designed and led the architecture of end-to-end ML systems using Azure ML Pipelines, automating model training, evaluation, registration, and deployment for business-critical decisioning services. Built distributed training loops for transformer-based LLMs and optimized fine-tuned models for summarization and RAG applications. Implemented vector stores and document chunking strategies supporting enterprise Q&A platforms. Orchestrated model lineage and lifecycle governance using MLflow and Azure ML with robust CI/CD pipelines containerized for AKS and autoscaling. Developed explainability frameworks with SHAP and LIME for customer churn and revenue models. Created scalable data transformation pipelines in Databricks using dbt. Led GenAI application deployments integrating LangChain and Azure OpenAI. Provided technical leadership across teams for vector DB integration, prompt design, and standardizing CI/CD workflows.

Senior Data Scientist at Virtusa Corporation

April 30, 2024 - July 21, 2025

Built scalable classification and regression models using LightGBM, XGBoost, and scikit-learn for credit risk and dynamic pricing. Fine-tuned transformer models like BERT for document classification. Developed deep learning pipelines to forecast time series demand integrating temporal embeddings and CNN layers. Automated ML workflows with Azure ML pipelines and MLflow tracking. Engineered advanced features using Pandas and Spark MLlib. Designed model explainability layers enabling risk score interpretation with SHAP and LIME. Optimized NLP pipelines with Spark NLP on Databricks. Deployed model inference containers in AKS. Managed reproducible experiments and orchestrated retraining with Airflow. Developed advanced SQL queries for feature engineering. Collaborated on CI/CD integrations within Azure DevOps. Led model review sessions supporting audit-ready documentation. Architected scalable GenAI systems involving vector embedding workflows and secure LLM querying.

Data Scientist at Mphasis

October 31, 2022 - July 21, 2025

Designed and deployed predictive models to optimize loan approval workflows using scikit-learn and XGBoost. Developed time series models in R and Python for retail demand forecasting with Tableau visualization. Queried large datasets using Hive and SQL enriching features for scoring pipelines. Automated model training pipelines with Airflow across AWS EMR and S3. Implemented anomaly detection frameworks using Isolation Forest in Hadoop environments. Created interactive notebooks for exploratory analysis and stakeholder presentations. Visualized model insights with matplotlib and Tableau. Engineered scalable ETL pipelines with PySpark and HiveQL. Managed version control using Git and consumed external REST APIs for feature enrichment. Applied feature selection and evaluated models with domain metrics and explainability techniques. Collaborated with DevOps for containerized batch scoring on AWS EMR.

Junior Data Scientist at Simform

June 30, 2020 - July 21, 2025

Developed regression models to analyze customer behavior and sales trends. Cleaned and transformed datasets leveraging Pandas and SQL with reusable workflows. Conducted EDA and visualizations using Matplotlib, Seaborn, and Jupyter Notebooks. Built validated statistical models in R for marketing effectiveness and A/B testing analysis. Applied hypothesis testing to support product decisions. Implemented clustering algorithms for customer segmentation. Automated recurring reports integrating Excel, SQL, and Python. Improved code readability and reproducibility. Collaborated on feature engineering to enhance model performance. Used Git for version control and delivered clear documentation and visual reports for stakeholders.