Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I am a data scientist and AI/ML engineer with over 7 years of experience building, deploying, and optimizing models that drive measurable business impact. I specialize in predictive analytics, big data processing, and end-to-end model lifecycle management, with hands-on experience in Python, R, SQL, TensorFlow, PyTorch, Spark, and AWS. I excel at designing customer segmentation, risk prediction, and fraud detection models, integrating ML into production with high availability and monitoring on cloud platforms. I enjoy collaborating with cross-functional teams and translating insights into strategic actions, backed by A/B testing, experimentation, and data storytelling.…I am a data scientist and AI/ML engineer with over 7 years of experience building, deploying, and optimizing models that drive measurable business impact. I specialize in predictive analytics, big data processing, and end-to-end model lifecycle management, with hands-on experience in Python, R, SQL, TensorFlow, PyTorch, Spark, and AWS. I excel at designing customer segmentation, risk prediction, and fraud detection models, integrating ML into production with high availability and monitoring on cloud platforms. I enjoy collaborating with cross-functional teams and translating insights into strategic actions, backed by A/B testing, experimentation, and data storytelling.

Sravani Reddy

Data Scientist, AI Engineer, AI Developer, +2





I am a data scientist and AI/ML engineer with over 7 years of experience building, deploying, and optimizing models that drive measurable business impact. I specialize in predictive analytics, big data processing, and end-to-end model lifecycle management, with hands-on experience in Python, R, SQL, TensorFlow, PyTorch, Spark, and AWS. I excel at designing customer segmentation, risk prediction, and fraud detection models, integrating ML into production with high availability and monitoring on cloud platforms. I enjoy collaborating with cross-functional teams and translating insights into strategic actions, backed by A/B testing, experimentation, and data storytelling.…I am a data scientist and AI/ML engineer with over 7 years of experience building, deploying, and optimizing models that drive measurable business impact. I specialize in predictive analytics, big data processing, and end-to-end model lifecycle management, with hands-on experience in Python, R, SQL, TensorFlow, PyTorch, Spark, and AWS. I excel at designing customer segmentation, risk prediction, and fraud detection models, integrating ML into production with high availability and monitoring on cloud platforms. I enjoy collaborating with cross-functional teams and translating insights into strategic actions, backed by A/B testing, experimentation, and data storytelling.

Available to hire

I am a data scientist and AI/ML engineer with over 7 years of experience building, deploying, and optimizing models that drive measurable business impact. I specialize in predictive analytics, big data processing, and end-to-end model lifecycle management, with hands-on experience in Python, R, SQL, TensorFlow, PyTorch, Spark, and AWS.

I excel at designing customer segmentation, risk prediction, and fraud detection models, integrating ML into production with high availability and monitoring on cloud platforms. I enjoy collaborating with cross-functional teams and translating insights into strategic actions, backed by A/B testing, experimentation, and data storytelling.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior Data Scientist at USAA

May 1, 2024 - November 24, 2025

Led the development and deployment of AI-driven predictive risk models to enhance fraud detection, underwriting accuracy, and financial forecasting using Python, scikit-learn, TensorFlow, and MLflow for experiment tracking. Designed and improved ML algorithms for credit and member risk assessment, reducing default prediction error rates by 15%. Analyzed large financial datasets to identify market trends and operational risks. Collaborated with engineering teams to integrate AI/ML models into production using AWS SageMaker, AWS Lambda, and Spark-based distributed systems. Conducted end-to-end A/B testing, model validation, and performance analysis, improving model stability and business impact. Utilized ML automation tools such as SageMaker Pipelines, Airflow, and Databricks Jobs to streamline feature engineering, model retraining, and monitoring.

Data Scientist at Bank of America

May 1, 2024 - May 1, 2024

Developed AI-driven predictive models to forecast customer behavior, credit patterns, and risk signals; built and automated end-to-end ETL pipelines with Python, SQL, and Airflow, reducing manual data management time by 30%. Performed comprehensive EDA and statistical analysis to uncover trends and improve risk management and fraud analytics. Enhanced customer segmentation using K-Means clustering with MLflow-tracked experiments, improving targeted marketing and engagement by 20%. Designed and deployed interactive AI-backed dashboards with Tableau and Power BI; leveraged AWS SageMaker for scalable model training, tuning, deployment, and monitoring. Applied PyTorch and deep learning techniques for advanced pattern detection in high-risk segments.

Data Scientist at Equinox Environments India Pvt. Ltd.

July 1, 2022 - July 1, 2022

Developed predictive models on patient health and clinical datasets, improving healthcare risk assessment accuracy. Performed comprehensive EDA to identify trends in patient behavior, enabling targeted retention strategies. Designed and automated ETL pipelines using Python and Apache Airflow, reducing processing time for analytics projects. Built and optimized ML and deep learning models for claims fraud detection, achieving a 20% reduction in fraudulent claims. Created interactive dashboards (Tableau) to communicate insights and model performance to clinical, operations, and leadership teams. Collaborated with cross-functional teams to deploy scalable analytics solutions on AWS, integrating cloud storage and distributed processing. Applied statistical modeling, feature engineering, and data cleaning to ensure data quality.

Data Scientist at ADP

June 1, 2020 - June 1, 2020

Explored and visualized large, complex datasets to uncover workforce and operational trends. Engineered forecasting models to analyze customer engagement and product usage, driving a 15% increase in retention. Streamlined data pipelines for high-volume HR datasets using Spark, PySpark, and AWS S3. Applied ML and deep learning to forecast product demand and improve inventory planning, reducing stockouts by 25%. Collaborated with cross-functional teams to deploy real-time analytics solutions employing Kafka and Hadoop. Automated feature engineering, data cleansing, and model training workflows to accelerate ML deployment cycles. Delivered dashboards and visual reports to support leadership decisions across HR, payroll, and workforce management.