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I am a Senior Data Scientist with 9+ years of experience delivering enterprise-scale AI/ML solutions across healthcare, banking, and fintech. I specialize in Python, PyTorch, TensorFlow, and Scikit-learn, focusing on production-grade model deployment and scalable ML pipelines. I have hands-on experience across AWS SageMaker, Azure ML, Databricks, MLflow, NLP, recommendations, and predictive analytics, with a track record of boosting fraud detection accuracy, customer engagement, and operational efficiency. I thrive in cross-functional teams and stay current with the latest AI trends such as LLMs and generative AI.\n\nI have led end-to-end ML projects in healthcare and financial services, built scalable data processing and feature stores, and developed explainable AI solutions to drive regulatory compliance and business impact.…I am a Senior Data Scientist with 9+ years of experience delivering enterprise-scale AI/ML solutions across healthcare, banking, and fintech. I specialize in Python, PyTorch, TensorFlow, and Scikit-learn, focusing on production-grade model deployment and scalable ML pipelines. I have hands-on experience across AWS SageMaker, Azure ML, Databricks, MLflow, NLP, recommendations, and predictive analytics, with a track record of boosting fraud detection accuracy, customer engagement, and operational efficiency. I thrive in cross-functional teams and stay current with the latest AI trends such as LLMs and generative AI.\n\nI have led end-to-end ML projects in healthcare and financial services, built scalable data processing and feature stores, and developed explainable AI solutions to drive regulatory compliance and business impact.

Naveena Voora

Data Scientist, AI Engineer, AI Developer, +2

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I am a Senior Data Scientist with 9+ years of experience delivering enterprise-scale AI/ML solutions across healthcare, banking, and fintech. I specialize in Python, PyTorch, TensorFlow, and Scikit-learn, focusing on production-grade model deployment and scalable ML pipelines. I have hands-on experience across AWS SageMaker, Azure ML, Databricks, MLflow, NLP, recommendations, and predictive analytics, with a track record of boosting fraud detection accuracy, customer engagement, and operational efficiency. I thrive in cross-functional teams and stay current with the latest AI trends such as LLMs and generative AI.\n\nI have led end-to-end ML projects in healthcare and financial services, built scalable data processing and feature stores, and developed explainable AI solutions to drive regulatory compliance and business impact.…I am a Senior Data Scientist with 9+ years of experience delivering enterprise-scale AI/ML solutions across healthcare, banking, and fintech. I specialize in Python, PyTorch, TensorFlow, and Scikit-learn, focusing on production-grade model deployment and scalable ML pipelines. I have hands-on experience across AWS SageMaker, Azure ML, Databricks, MLflow, NLP, recommendations, and predictive analytics, with a track record of boosting fraud detection accuracy, customer engagement, and operational efficiency. I thrive in cross-functional teams and stay current with the latest AI trends such as LLMs and generative AI.\n\nI have led end-to-end ML projects in healthcare and financial services, built scalable data processing and feature stores, and developed explainable AI solutions to drive regulatory compliance and business impact.

Available to hire

I am a Senior Data Scientist with 9+ years of experience delivering enterprise-scale AI/ML solutions across healthcare, banking, and fintech. I specialize in Python, PyTorch, TensorFlow, and Scikit-learn, focusing on production-grade model deployment and scalable ML pipelines. I have hands-on experience across AWS SageMaker, Azure ML, Databricks, MLflow, NLP, recommendations, and predictive analytics, with a track record of boosting fraud detection accuracy, customer engagement, and operational efficiency. I thrive in cross-functional teams and stay current with the latest AI trends such as LLMs and generative AI.\n\nI have led end-to-end ML projects in healthcare and financial services, built scalable data processing and feature stores, and developed explainable AI solutions to drive regulatory compliance and business impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

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Expert

Work Experience

Senior Data Scientist at Fifth Third Bank

October 1, 2025 - Present

Designed and deployed real-time fraud detection models using XGBoost (1.7+) and PyTorch (2.x) on high-volume transaction streams, improving fraud detection accuracy by 32% while reducing false positives through advanced feature engineering and threshold optimization techniques. Architected scalable end-to-end ML pipelines using AWS SageMaker, Apache Spark (3.4+), and Delta Lake, enabling distributed data processing and reducing model training and inference latency by 40% across enterprise datasets. Built high-performance inference APIs using FastAPI, Docker (24.x), and Kubernetes (1.28+), ensuring low-latency predictions (<100ms) and 99.9% service uptime in production environments. Implemented robust feature stores using AWS S3, Snowflake, and Redis caching layers, improving feature reuse and reducing redundant computations by 35%.

Data Scientist at Cigna

January 1, 2024 - September 30, 2025

Developed and deployed predictive healthcare models using TensorFlow (2.15+) and Scikit-learn (1.3+), improving patient risk stratification accuracy by 28% and enabling proactive care interventions across large member populations. Designed NLP pipelines using BERT/BioBERT and Transformers (4.x) to extract insights from clinical notes, reducing manual review efforts by 45%. Built scalable ML pipelines using Azure ML (v2), Databricks (Runtime 13.x), and Spark (3.3+), enabling distributed processing and reducing model training time by 35%. Implemented MLOps with MLflow (2.x), Azure DevOps, and GitHub Actions, automating model versioning, tracking, and deployment. Engineered feature extraction pipelines with Python, Pandas, and NumPy, improving performance by 20%. Developed deep learning models in PyTorch for patient outcomes, integrated real-time data ingestion with Kafka, and created Power BI/Tableau dashboards. Ensured explainability with SHAP and LIME for regulatory compliance, and col

Senior Data Scientist at Pipal Solutions (India) Pvt. Ltd

October 1, 2021 - July 31, 2023

Designed and implemented large-scale recommendation systems using collaborative filtering, matrix factorization, and deep learning models (TensorFlow 2.x, Keras), achieving 30% improvement in customer conversion and enhanced personalization. Built distributed data pipelines using Apache Spark (3.2+), Hadoop, and Hive; implemented real-time data ingestion and streaming architectures with Kafka. Established end-to-end MLOps with MLflow (1.x/2.x), Jenkins, and Docker (20.x+), reducing release cycles by 45%. Engineered feature pipelines with Python (3.8+), Pandas, and NumPy; deployed NLP solutions using Hugging Face Transformers and BERT models; built data warehouses with Snowflake and PostgreSQL; created dashboards with Tableau/Power BI; applied statistical modeling with SciPy/Statsmodels. Collaborated in Agile/Scrum environments and mentored junior data scientists.

Data Scientist at OrbiTech Solutions Limited

September 1, 2019 - June 30, 2021

Developed predictive analytics models using Scikit-learn, XGBoost, and Random Forest; built end-to-end data pipelines with Python, Pandas, and SQL Server; designed and optimized ETL workflows; implemented feature engineering and model deployment via REST APIs. Built dashboards using Tableau/Power BI and performed NLP tasks with NLTK/SpaCy. Collaborated with data engineering to integrate Apache Spark for large-scale datasets and conducted statistical analyses using SciPy/Statsmodels. Maintained version control with Git and participated in Agile ceremonies to deliver analytics solutions.

Junior Data Scientist at Nihilent Technologies Pvt Ltd

July 1, 2016 - August 31, 2019

Developed foundational ML models using Scikit-learn (0.20+), including Logistic Regression, Decision Trees, and KNN; performed extensive data preprocessing and EDA; built SQL queries for data extraction and reporting. Contributed to classification and regression models for customer segmentation and churn prediction; implemented feature engineering techniques, and deployed ML models via Flask-based APIs. Built dashboards with Tableau/Excel and supported Agile, version control with Git, and documentation of model workflows and data pipelines.