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Vindhya H V

@vindhyahv

Data Scientist at Ericsson Global India, developing netsales forecasting and an AWS Bedrock platform for automated variance analysis.

India

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What I'm looking for

I'm seeking a challenging position in data science at a dynamic organization where I can apply and enhance my skills while contributing to the company's success.

At Ericsson Global India, I developed a netsales forecasting system using statistical regression models and historical business and market data. I used AWS EC2 for compute, AWS S3 for storage, and MLflow for experiment tracking and model versioning.

I also developed a platform that automates variance analysis, using AWS Bedrock LLMs to generate audit-ready explanations for anomalies. It uses a Next.js frontend and Flask APIs.

At Western Digital (SanDisk), I developed and deployed an XGBoost model to classify drives by health status. I also analyzed historic log data with Isolation Forest, hypothesis testing, t-tests, and chi-squared tests.

At Western Digital (SanDisk), I designed and developed a dashboard and deployed models to Amazon EKS, monitoring them with Argo, Grafana, and Splunk. Earlier, as a Machine Learning Engineer at Accenture, I developed and deployed an NLP-based model to classify contractual documents as risky or non-risky.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Ericsson Global India

Feb 2025 - Present (1 year 8 months)

Developed a robust netsales forecasting system using statistical regression models and built a platform for automated variance analysis using LLMs via AWS Bedrock.

regression EC2 S3 MLFlow LLM AWS Next.js Flask

Current

Data Scientist 2

Current

Western Digital (SanDisk)

Jul 2022 - Present (4 years 3 months)

Developed and deployed a boosting model using XGBoost for drive classification and performed population analysis with anomaly detection and statistical testing. Led the design of a dynamic dashboard using Next.js and deployed models to Amazon EKS.

XGBoost Machine Learning Anomaly Detection Isolation Forest Hypothesis Testing T Test Chi Squared Next.js Amazon EKS Argo Grafana Splunk

Machine Learning Engineer

Accenture

Jul 2019 - Jul 2022 (3 years)

Developed and deployed a document classification model to categorize contractual documents as risky or non-risky using NLP, cluster analysis, and logistic regression.

NLP Cluster Analysis Logistic Regression Document Classification