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I'm Ramya Sri Tellakula, a data scientist and AI/ML engineer with 4+ years of experience designing, training, and deploying machine learning models in production cloud environments. I specialize in Python, PySpark, NLP, MLOps, and scalable data pipelines across AWS and Azure to deliver explainable, compliant, high-impact AI solutions in fintech and manufacturing. I enjoy turning complex data into actionable business insights, collaborating with cross-functional teams, and delivering measurable improvements in model accuracy, operational efficiency, and business outcomes. I am passionate about responsible AI, security, and operational excellence, and I continuously evolve my skills through hands-on experimentation, monitoring, and retraining to ensure robust, compliant deployments.…I'm Ramya Sri Tellakula, a data scientist and AI/ML engineer with 4+ years of experience designing, training, and deploying machine learning models in production cloud environments. I specialize in Python, PySpark, NLP, MLOps, and scalable data pipelines across AWS and Azure to deliver explainable, compliant, high-impact AI solutions in fintech and manufacturing. I enjoy turning complex data into actionable business insights, collaborating with cross-functional teams, and delivering measurable improvements in model accuracy, operational efficiency, and business outcomes. I am passionate about responsible AI, security, and operational excellence, and I continuously evolve my skills through hands-on experimentation, monitoring, and retraining to ensure robust, compliant deployments.

Ramya Sri Tellakula

Data Scientist, AI Engineer, Data Analyst, +2

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I'm Ramya Sri Tellakula, a data scientist and AI/ML engineer with 4+ years of experience designing, training, and deploying machine learning models in production cloud environments. I specialize in Python, PySpark, NLP, MLOps, and scalable data pipelines across AWS and Azure to deliver explainable, compliant, high-impact AI solutions in fintech and manufacturing. I enjoy turning complex data into actionable business insights, collaborating with cross-functional teams, and delivering measurable improvements in model accuracy, operational efficiency, and business outcomes. I am passionate about responsible AI, security, and operational excellence, and I continuously evolve my skills through hands-on experimentation, monitoring, and retraining to ensure robust, compliant deployments.…I'm Ramya Sri Tellakula, a data scientist and AI/ML engineer with 4+ years of experience designing, training, and deploying machine learning models in production cloud environments. I specialize in Python, PySpark, NLP, MLOps, and scalable data pipelines across AWS and Azure to deliver explainable, compliant, high-impact AI solutions in fintech and manufacturing. I enjoy turning complex data into actionable business insights, collaborating with cross-functional teams, and delivering measurable improvements in model accuracy, operational efficiency, and business outcomes. I am passionate about responsible AI, security, and operational excellence, and I continuously evolve my skills through hands-on experimentation, monitoring, and retraining to ensure robust, compliant deployments.

Available to hire

I’m Ramya Sri Tellakula, a data scientist and AI/ML engineer with 4+ years of experience designing, training, and deploying machine learning models in production cloud environments. I specialize in Python, PySpark, NLP, MLOps, and scalable data pipelines across AWS and Azure to deliver explainable, compliant, high-impact AI solutions in fintech and manufacturing. I enjoy turning complex data into actionable business insights, collaborating with cross-functional teams, and delivering measurable improvements in model accuracy, operational efficiency, and business outcomes.

I am passionate about responsible AI, security, and operational excellence, and I continuously evolve my skills through hands-on experimentation, monitoring, and retraining to ensure robust, compliant deployments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AI/ML Engineer at Plaid Inc.

January 1, 2025 - Present

Designed and deployed FinSight AI, an AI-driven financial insights platform leveraging transaction classification, anomaly detection, and recommendation models, improving fraud detection precision by 18%. Built scalable ETL pipelines using Apache Airflow, Python, and AWS Glue to process high-volume financial transaction data, reducing data quality issues and ETL failures by 25%. Developed user and transaction embeddings to model spending behavior and merchant risk, reducing anomaly detection false positives by 32% and improving recommendation relevance by 22%. Fine-tuned transformer-based LLMs (BERT, DeBERTa) on AWS SageMaker, increasing ranking relevance (NDCG@10 from 0.54 to 0.80) and improving predictive accuracy by 20%. Implemented parameter-efficient fine-tuning (LoRA) using Hugging Face, Accelerate, and DeepSpeed, reducing inference cost and manual review time by 35% while maintaining SOC 2 & PCI DSS compliance. Deployed containerized ML services using Docker and Kubernetes (EKS)

Data Scientist / Machine Learning Engineer at Novelis

May 1, 2024 - December 1, 2024

Built predictive maintenance models (Random Forest, LSTM) using IoT sensor data across 7 manufacturing plants, improving failure prediction accuracy by 22% and reducing unplanned downtime by 15%. Engineered real-time anomaly detection pipelines using PySpark on Azure Databricks, enabling automated alerts and reducing incident response time by 20%. Fine-tuned BERT and DistilBERT models for incident and maintenance log classification, achieving 93% precision. Deployed models using Azure Machine Learning with CI/CD pipelines, monitoring, retraining triggers, and version control. Delivered Power BI dashboards with SHAP and LIME explainability, increasing business adoption of ML insights by 30%.

Data Scientist / Machine Learning Engineer at Tata Consultancy Services Ltd (Client: Novelis)

January 1, 2021 - August 1, 2023

Led enterprise analytics modernization, designing end-to-end data pipelines integrating SQL Server, Azure SQL, and Power BI, improving reporting speed and decision visibility by 45%. Designed and deployed ML solutions for ticket classification, customer segmentation, and forecasting, improving prediction accuracy by 25% and operational efficiency by 20%. Built supervised ML models using Scikit-learn, XGBoost, and Logistic Regression, optimizing performance via cross-validation and hyperparameter tuning. Delivered NLP automation solutions using TF-IDF, embeddings, spaCy, BERTopic, reducing manual ticket triage effort by 40% and SLA breaches by 22%. Implemented Azure ML MLOps pipelines for preprocessing, training, deployment, monitoring, and drift detection, ensuring 99% system uptime.