I am a results-driven Data Scientist with over 3 years of experience specializing in machine learning, data analysis, and cloud-based model deployment. I enjoy designing scalable AI solutions and leveraging tools like Python, TensorFlow, and big data technologies to deliver actionable insights that optimize business performance. My experience spans multiple industries including finance and healthcare, where I've built robust models and recommendation systems. I'm skilled in working with cloud platforms such as AWS and Azure to deploy and automate models for real-time analytics. I’m passionate about using advanced algorithms and reinforcement learning to tackle complex challenges and help organizations make data-driven investment and healthcare decisions.

Gagan Chandra Motamarri

I am a results-driven Data Scientist with over 3 years of experience specializing in machine learning, data analysis, and cloud-based model deployment. I enjoy designing scalable AI solutions and leveraging tools like Python, TensorFlow, and big data technologies to deliver actionable insights that optimize business performance. My experience spans multiple industries including finance and healthcare, where I've built robust models and recommendation systems. I'm skilled in working with cloud platforms such as AWS and Azure to deploy and automate models for real-time analytics. I’m passionate about using advanced algorithms and reinforcement learning to tackle complex challenges and help organizations make data-driven investment and healthcare decisions.

Available to hire

I am a results-driven Data Scientist with over 3 years of experience specializing in machine learning, data analysis, and cloud-based model deployment. I enjoy designing scalable AI solutions and leveraging tools like Python, TensorFlow, and big data technologies to deliver actionable insights that optimize business performance. My experience spans multiple industries including finance and healthcare, where I’ve built robust models and recommendation systems.

I’m skilled in working with cloud platforms such as AWS and Azure to deploy and automate models for real-time analytics. I’m passionate about using advanced algorithms and reinforcement learning to tackle complex challenges and help organizations make data-driven investment and healthcare decisions.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Data Scientist at Fidelity Investments
October 1, 2024 - Present
Designed and implemented an AI-driven portfolio optimization system using PyPortfolioOpt and TensorFlow. Integrated multi-source financial datasets via SQL to construct dynamic, risk-adjusted investment strategies for diverse market scenarios. Applied Deep Q-Networks (DQN), a reinforcement learning model, to create adaptive investment strategies. Used AWS SageMaker pipelines for model training, evaluation, and tuning, ensuring effective handling of market volatility and trend shifts. Developed and tested models using historical market data from Quandl and live feeds from Alpha Vantage, achieving consistent outperformance over benchmark indices. Incorporated risk management models such as Value at Risk (VaR) and Conditional VaR (CVaR). Automated computation of risk thresholds to ensure portfolio robustness while optimizing returns. Deployed models on Amazon EKS for real-time predictions and managed preprocessing with AWS Glue and AWS EMR. Achieved a 22% improvement in portfolio returns
Data Scientist at Firstsource Healthcare
August 31, 2023 - August 1, 2025
Developed a Personalized Healthcare Recommendation System by integrating patient history, demographics, and browsing data using SQL and Spark. Designed collaborative filtering (Matrix Factorization) and content-based recommendation models with LightFM and Surprise, incorporating patient and product metadata. Conducted thorough data preprocessing including handling missing values and encoding categorical variables, enabling robust model training tailored to individual patient needs. Applied GridSearchCV and Bayesian optimization for hyperparameter tuning, improving recommendation accuracy by 20% and enhancing system efficiency. Trained models using k-fold cross-validation, achieving a 92% accuracy rate in predicting healthcare product recommendations. Deployed the system on Azure infrastructure using Blob Storage, Azure Functions, and AKS for scalable real-time operation. Created Power BI dashboards to visualize performance and patient engagement, driving a 30% increase in service satis

Education

Master of Science at University of Colorado Boulder, Colorado, USA
August 1, 2023 - May 31, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Financial Services, Healthcare, Software & Internet