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I am Rohith Sai Gude, a data scientist with over four years of experience turning raw data into actionable insights using Python, R, and SQL. I enjoy building data-driven solutions that improve decision-making and operational efficiency. I have hands-on experience with big data tools like Spark, Kafka, and Databricks, and cloud platforms AWS, Azure, and GCP. I design scalable, explainable models and deploy production-grade systems using Docker, Kubernetes, and MLflow, with a focus on governance and reliability.…I am Rohith Sai Gude, a data scientist with over four years of experience turning raw data into actionable insights using Python, R, and SQL. I enjoy building data-driven solutions that improve decision-making and operational efficiency. I have hands-on experience with big data tools like Spark, Kafka, and Databricks, and cloud platforms AWS, Azure, and GCP. I design scalable, explainable models and deploy production-grade systems using Docker, Kubernetes, and MLflow, with a focus on governance and reliability.

Rohith Sai Gude

Data Scientist, AI Engineer, AI Developer, +2

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I am Rohith Sai Gude, a data scientist with over four years of experience turning raw data into actionable insights using Python, R, and SQL. I enjoy building data-driven solutions that improve decision-making and operational efficiency. I have hands-on experience with big data tools like Spark, Kafka, and Databricks, and cloud platforms AWS, Azure, and GCP. I design scalable, explainable models and deploy production-grade systems using Docker, Kubernetes, and MLflow, with a focus on governance and reliability.…I am Rohith Sai Gude, a data scientist with over four years of experience turning raw data into actionable insights using Python, R, and SQL. I enjoy building data-driven solutions that improve decision-making and operational efficiency. I have hands-on experience with big data tools like Spark, Kafka, and Databricks, and cloud platforms AWS, Azure, and GCP. I design scalable, explainable models and deploy production-grade systems using Docker, Kubernetes, and MLflow, with a focus on governance and reliability.

Available to hire

I am Rohith Sai Gude, a data scientist with over four years of experience turning raw data into actionable insights using Python, R, and SQL. I enjoy building data-driven solutions that improve decision-making and operational efficiency.

I have hands-on experience with big data tools like Spark, Kafka, and Databricks, and cloud platforms AWS, Azure, and GCP. I design scalable, explainable models and deploy production-grade systems using Docker, Kubernetes, and MLflow, with a focus on governance and reliability.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Data Scientist at Intuit

February 1, 2025 - Present

Led real-time data streaming and analytics enhancements using Kafka and AWS Lambda; reduced reporting delays by 50% and improved analytics response times. Implemented ensemble models (XGBoost, CatBoost) to stabilize retention predictions, increasing accuracy by 15%. Introduced SHAP and LIME to improve model interpretability, boosting adoption by business users by 20%. Automated executive dashboards in Tableau with live retention and churn metrics; strengthened A/B testing frameworks; implemented model monitoring with Evidently AI and Prometheus to reduce production drift by 30%. Containerized APIs with FastAPI and Docker to achieve 99% uptime. Built a real-time event-driven pipeline using Kafka and AWS Lambda to cut data processing latency by 50%.

Data Scientist at Borland Software

March 1, 2020 - November 1, 2022

Developed recommendation systems using collaborative filtering and matrix factorization to boost user engagement by 18%. Built customer segmentation with K-Means, DBSCAN, and PCA to improve marketing targeting. Implemented predictive maintenance models (Random Forest, XGBoost) reducing downtime by 25%. Enhanced personalization via matrix factorization; accelerated data pipelines by reengineering Spark and Databricks ETL with Delta Lake validation (40% faster). Improved forecasting with ARIMA, LSTM, Prophet by 15% reliability. Automated retraining and monitoring with Airflow; improved reproducibility with versioning and lineage; delivered Power BI dashboards linking model results to key metrics; reduced data processing time 30% by optimizing queries; standardized ML workflows with MLflow and Feature Store.