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I am a Machine Learning Engineer with 3 years of experience specializing in the insurance and analytics domains. I deliver end-to-end solutions including data preprocessing, feature engineering, model development, deployment, and monitoring. My expertise spans MLOps, NLP, and large language models, and I am proficient in building scalable ML pipelines, RAG architectures, and RESTful APIs using technologies like Python, PyTorch, FastAPI, and Azure. I have a proven track record in model drift detection, CI/CD automation, and cloud-based deployments that empower business teams to improve decision-making, enhance customer retention, and streamline workflow automation. I thrive in collaborative environments, partnering with product managers and engineers to integrate ML solutions that enable real-time services and faster claim resolutions.…I am a Machine Learning Engineer with 3 years of experience specializing in the insurance and analytics domains. I deliver end-to-end solutions including data preprocessing, feature engineering, model development, deployment, and monitoring. My expertise spans MLOps, NLP, and large language models, and I am proficient in building scalable ML pipelines, RAG architectures, and RESTful APIs using technologies like Python, PyTorch, FastAPI, and Azure. I have a proven track record in model drift detection, CI/CD automation, and cloud-based deployments that empower business teams to improve decision-making, enhance customer retention, and streamline workflow automation. I thrive in collaborative environments, partnering with product managers and engineers to integrate ML solutions that enable real-time services and faster claim resolutions.

Pranay Kumar Reddy Chamala

Developer, AI Engineer, Data Analyst, +3

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I am a Machine Learning Engineer with 3 years of experience specializing in the insurance and analytics domains. I deliver end-to-end solutions including data preprocessing, feature engineering, model development, deployment, and monitoring. My expertise spans MLOps, NLP, and large language models, and I am proficient in building scalable ML pipelines, RAG architectures, and RESTful APIs using technologies like Python, PyTorch, FastAPI, and Azure. I have a proven track record in model drift detection, CI/CD automation, and cloud-based deployments that empower business teams to improve decision-making, enhance customer retention, and streamline workflow automation. I thrive in collaborative environments, partnering with product managers and engineers to integrate ML solutions that enable real-time services and faster claim resolutions.…I am a Machine Learning Engineer with 3 years of experience specializing in the insurance and analytics domains. I deliver end-to-end solutions including data preprocessing, feature engineering, model development, deployment, and monitoring. My expertise spans MLOps, NLP, and large language models, and I am proficient in building scalable ML pipelines, RAG architectures, and RESTful APIs using technologies like Python, PyTorch, FastAPI, and Azure. I have a proven track record in model drift detection, CI/CD automation, and cloud-based deployments that empower business teams to improve decision-making, enhance customer retention, and streamline workflow automation. I thrive in collaborative environments, partnering with product managers and engineers to integrate ML solutions that enable real-time services and faster claim resolutions.

Available to hire

I am a Machine Learning Engineer with 3 years of experience specializing in the insurance and analytics domains. I deliver end-to-end solutions including data preprocessing, feature engineering, model development, deployment, and monitoring. My expertise spans MLOps, NLP, and large language models, and I am proficient in building scalable ML pipelines, RAG architectures, and RESTful APIs using technologies like Python, PyTorch, FastAPI, and Azure.

I have a proven track record in model drift detection, CI/CD automation, and cloud-based deployments that empower business teams to improve decision-making, enhance customer retention, and streamline workflow automation. I thrive in collaborative environments, partnering with product managers and engineers to integrate ML solutions that enable real-time services and faster claim resolutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Machine Learning Engineer at MetLife

March 1, 2025 - Present

Designed and deployed classification models to segment policyholders and predict churn risk, improving retention targeting by 28%. Developed transformer-based summarization models (BERT, T5, Pegasus) to process insurance documents and claim summaries, reducing manual review time by 40%. Engineered retrieval-augmented generation pipelines integrating FAISS and Hugging Face Transformers to answer claim-related queries, decreasing agent response time by 35%. Built low-latency RESTful inference APIs with FastAPI and Docker, scaled with Kubernetes (EKS) for real-time chatbot services. Automated model retraining and CI/CD workflows using GitHub Actions, MLflow, and Docker; included EvidentlyAI for drift detection and seamless retraining. Collaborated with product managers and engineers to integrate ML APIs into customer-facing applications, accelerating claim resolutions by 20%.

Machine Learning Engineer at MetLife – USA

March 1, 2025 - Present

Designed and deployed classification models that improved policyholder segmentation and churn risk prediction, increasing retention targeting by 28%. Developed transformer-based document summarization models which reduced manual review time by 40%. Built RAG pipelines for claims queries, reducing agent response time by 35%. Delivered low-latency inference APIs using FastAPI, Docker, and Kubernetes for real-time chatbot services. Automated model retraining and CI/CD workflows integrating drift detection with EvidentlyAI to ensure model reliability. Collaborated cross-functionally to embed ML APIs into customer-facing platforms, accelerating claim resolution by 20%.

Machine Learning Engineer at MetLife, USA

March 1, 2025 - Present

Developed classification models to segment policyholders and flag churn risk, improving retention targeting by 28%. Built transformer-based summarization models (BERT, T5) to automate insurance document processing and claims summary. Engineered RAG pipelines with Hugging Face and FAISS to answer claim-related queries, enhancing agent response by 35%. Exposed RESTful chatbot inference APIs using FastAPI for real-time customer service across digital channels. Automated retraining workflows using GitHub Actions, Docker, and MLflow to track versioning and manage model drift.

Data Analyst at Capgemini, India

August 31, 2023 - July 18, 2025

Built executive dashboards using Tableau and Spotfire to visualize churn, sales, and service trends across B2B clients. Automated ETL pipelines with SQL and Python to process over 1M records weekly, reducing data preparation time by 40%. Conducted A/B testing on digital campaigns and landing pages, identifying winning variants and increasing conversion by 12%. Conducted customer segmentation using k-means and feature engineering to support targeted marketing strategies. Created time series forecasts using ARIMA and Prophet, improving demand planning accuracy by 20%. Integrated ML insights into BI dashboards, enabling predictive alerting for business KPIs. Developed churn prediction models with scikit-learn and embedded outputs into stakeholder reporting workflows. Partnered with business users to define KPIs and iterate on analytical models that improved campaign ROI by 15%.

Data Analyst at Capgemini

August 1, 2023 - August 27, 2025

Automated ETL pipelines processing over 1 million records weekly using Python and SQL, reducing data preparation time by 40%. Conducted A/B testing on digital campaigns, identifying high-performing variants which increased conversions by 12%. Developed customer segmentation models (k-means) and feature engineering pipelines to support targeted marketing strategies for B2B clients. Implemented churn prediction models in scikit-learn and integrated results into Tableau dashboards to aid retention strategies. Delivered time series forecasts (ARIMA, Prophet) improving demand planning accuracy by 20%. Created executive dashboards in Tableau and Spotfire embedding ML insights and predictive alerts for key performance indicators. Partnered with stakeholders to define KPIs and refine models, enhancing campaign ROI by 15%.

Data Analyst at Capgemini – India

August 1, 2023 - August 27, 2025

Automated ETL pipelines processing over 1 million records weekly, reducing data preparation time by 40%. Executed A/B testing on digital campaigns identifying high-performing variants, boosting conversion rates by 12%. Developed customer segmentation models and feature engineering pipelines to aid targeted marketing. Implemented churn prediction and integrated results into Tableau dashboards supporting retention strategies. Delivered time series forecasts improving demand planning accuracy by 20%. Created executive dashboards visualizing ML insights and predictive alerts for KPIs. Partnered with stakeholders to define KPIs and refine models, improving campaign ROI by 15%.

Machine Learning Engineer Intern at Hexaware Technologies, India

July 31, 2021 - July 18, 2025

Trained logistic regression and decision tree models on product feedback datasets to identify churn-prone users. Performed data preprocessing, EDA, and feature selection using Pandas and scikit-learn for initial model development. Built prototype dashboards in Streamlit to present model outputs to internal stakeholders. Documented model logic, assumptions, and limitations to assist transition to production teams.

Machine Learning Engineer Intern at Hexaware Technologies

July 1, 2021 - August 27, 2025

Trained and evaluated logistic regression and decision tree models on product feedback datasets to identify churn-prone users. Conducted data preprocessing, feature selection, and exploratory data analysis ensuring model-quality inputs. Created prototype dashboards using Streamlit for internal stakeholder review of model outputs. Documented model assumptions, limitations, and performance metrics facilitating smooth handoff to production teams.

Machine Learning Engineer Intern at Hexaware Technologies – India

July 1, 2021 - August 27, 2025

Trained and evaluated logistic regression and decision tree models to identify churn-prone users. Conducted data preprocessing, feature selection, and exploratory data analysis ensuring robust data for modeling. Developed prototype dashboards using Streamlit to visualize models for stakeholders. Documented model assumptions, limitations, and performance metrics facilitating smooth production handoffs.