---
title: "Sai Rajesh Rapelli - Data Science Engineer in Hyderabad | Tal"
description: "Meet Sai Rajesh Rapelli, Data Science Engineer | Driving AI Innovation in Solid Waste Management at Avartan Labs based in Hyderabad. AI stack includes claude code, geminicli, and hugging face."
image: "https://tal.club/meet/sai-rajesh-rapelli/share-image"
---

# Sai Rajesh Rapelli on Tal

## Headline

Data Science Engineer \| Driving AI Innovation in Solid Waste Management at Avartan Labs

## Location

Hyderabad

## AI stack

claude code

geminicli

hugging face

## Work experience

Data Science Engineer at Avartan Labs, Mar 2026 \- Present · 8 mos, – Develop, deploy, and optimize AI/ML models for waste segregation, garbage surveillance, and route planning\. – Build and manage scalable data pipelines, MLOps workflows, and analytics platforms\. – Oversee the complete model lifecycle including data acquisition, feature engineering, training, deployment, monitoring, and retraining\. – Participate in prototyping, on\-site testing, and performance trials to ensure reliability and robustness\. – Collaborate cross\-functionally with engineers, customers, investors, and ecosystem partners to drive product innovation\.

Research Data Engineer at University of Maryland Baltimore County, Jan 2024 \- Dec 2025 · 2 yrs, Project: Navy Obsolescence Prediction \(Post\-Graduate contract extension\) Technologies: Azure Data Factory, Azure Data Lake Storage Gen2, Databricks, Python, SQL – Built Azure Data Factory pipelines using Copy Data, Lookup, and ForEach activities to ingest high\-frequency sensor and voltage data from source systems into Azure Data Lake Storage Gen2\. – Implemented medallion architecture pipelines using Delta Lake to support analytics and downstream machine learning workflows\. – Automated recurring transformation workflows using scheduled triggers, reducing manual data preparation effort by 50%\. Project: CO2 Emission Forecasting Pipeline Technologies: Azure Data Factory, Databricks, Python, Deep Learning – Designed end\-to\-end ETL pipelines in Azure Data Factory to ingest, clean, and transform high\-frequency time\-series sensor data\. – Developed PySpark preprocessing workflows involving feature selection, time\-series sequence preparation, data reshaping, and output transformation to support LSTM\-based modeling\. – Assisted with monitoring ADF pipeline runs and alerts, helping ensure timely ingestion of sensor data for analytics\. – Published peer\-reviewed research titled “A LSTM with Dual\-stage Attention Method to Predict Amine Emissions for Carbon Dioxide Capture and Storage”\.

Application Developer at Accenture, Sep 2021 \- Jan 2023 · 1 yr 5 mos, Project: WEC Energy Resource Management and Incident Reporting Platform Technologies: Excel, SQL, MS SQL Server, Power BI – Used MS SQL Server queries to track and report daily incident counts and operational metrics for the team\. – Maintained resource, incident, and audit data in Azure Data Lake Storage, organizing data into raw and curated layers\. – Supported data ingestion by moving on\-premises operational and incident data into Azure Blob Storage\. – Supported ETL workflows and prepared data for Power BI and Excel dashboards, updating metrics in Accenture internal tools \(MyWizard and SMART\)\.

## Education

Master's degree, Information Systems, University of Maryland Baltimore County

Bachelor of Technology \- BTech, Electronics and Communications Engineering, Vignan institute of technology and science

[View the original profile](https://tal.club/meet/sai-rajesh-rapelli)

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