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Karthikeya PervelaKP
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Karthikeya Pervela

@karthikeyapervela

Data Scientist specializing in end-to-end ML systems, recommendation engines. I build scalable, production-ready solutions.

India
Message

What I'm looking for

I am looking for a role that fosters innovation and collaboration, where I can apply my data science skills to solve real-world problems and contribute to impactful projects.

Data Scientist with 2+ years of experience building production-grade ML systems, from feature engineering to A/B testing and deployment. At EloElo, I built a personalized short-video recommendation system from scratch, delivering +1.85% D1 retention lift via online A/B experiments. I engineered features using PySpark on EMR Serverless, built an online feature store (ScyllaDB) for sub-50ms inference, and containerized the scoring API for AWS ECS. I replaced p-value reporting with bootstrap-based lift probability for faster decisions. Previously at Saint-Gobain, I developed cost-sensitive XGBoost models on IoT sensor data, improving defect recall to 84% and reducing unacceptable batches by 14%. I also built a constraint-programming optimization system that improved material utilization to 95% and cut waste by 50%. I hold an M.Tech from IIT Kanpur, with expertise in ML, statistics, and optimization. Passionate about scalable, data-driven solutions for complex business challenges

Experience

Work history, roles, and key accomplishments

EL
Current

Data Scientist

Eloelo

Sep 2025 - Present (10 months)

Built a personalized short-video recommendation system from scratch—designed custom loss functions, engineered behavioral features with PySpark on EMR, deployed a sub-50ms scoring API with ScyllaDB, and validated +1.85% retention lift through online A/B experiments. Replaced p-value reporting with bootstrap-based lift probability for faster decision-making.

Education

Degrees, certifications, and relevant coursework

Indian Institute of Technology, Kanpur logoIK

Indian Institute of Technology, Kanpur

Master of Technology, Machine Learning

2021 - 2023

Focused on the application of Machine Learning for materials property prediction, with relevant courses in Machine Learning, Mathematics, and Computational Methods.

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