---
title: "Ayesha Banu - Analyst - AI/ML in India | Tal"
description: "Meet Ayesha Banu, Gold Medalist MSc CS | Applied AI & ML Analyst @ Continual Engine | Document AI • Machine Learning • NLP • Python • SQL • Power BI based in India."
image: "https://tal.club/meet/ayesha-7/share-image"
---

# Ayesha Banu on Tal

## Headline

Gold Medalist MSc CS \| Applied AI & ML Analyst @ Continual Engine \| Document AI • Machine Learning • NLP • Python • SQL • Power BI

## About

I enjoy building AI and data\-driven solutions that turn complex data into practical business insights\. Currently working as an Analyst \(AI/ML\) at Continual Engine, I contribute to large\-scale Document AI workflows involving CVAT annotation, structured output validation, PDF\-to\-HTML testing, JSON validation, and AI model evaluation for accessibility\-focused systems\. My experience includes Applied AI, Machine Learning, NLP, and analytics projects across Telecom, HR, Retail, and Customer Intelligence domains using Python, Scikit\-learn, TensorFlow, SQL, Power BI, and Streamlit\. Some of my work includes: • Multimodal AI for Telecom Churn & Sentiment Analysis • XGBoost models with SHAP explainability • CNN \+ BiLSTM sentiment analysis pipelines • Interactive Power BI dashboards and Streamlit applications • AI validation and structured output evaluation workflows • Analytics projects in HR, Retail, Inventory, and CRM domains I’m particularly interested in Applied AI, Document AI, Machine Learning, NLP, AI Evaluation, and Data Analytics roles where I can continue building practical AI solutions and solving real\-world business problems\. 📩 Feel free to connect with me here on LinkedIn or reach out at: ayesha24banu@gmail\.com

## Location

India

## Work experience

Analyst \- AI/ML at Continual Engine, Feb 2026 \- Present · 5 mos, India, • Annotated and validated 10,000\+ document pages using CVAT for large\-scale Document AI systems, including titles, headings, tables, lists, figures, and structured layouts\. • Supported accessibility\-focused AI systems for visually impaired users by validating structured outputs and document understanding workflows across complex layouts\. • Validated 200\+ AI model predictions and 2,000\+ annotated elements against ground truth, achieving \~95% annotation accuracy through QA and consistency checks\. • Performed PDF\-to\-HTML and JSON validation across 500\+ PDFs, improving layout reliability through structural and reading\-order verification\. • Evaluated structured outputs using PREP tools for headings, paragraphs, lists, tables, and figures while generating Excel\-based QA reports for issue tracking and model analysis\. • Collected and organized 3,000\+ training datasets across 400\+ PDFs and identified 30\+ critical annotation and structural issues while collaborating with AI/ML engineers and QA teams\.

Data Science Intern at Oasis Infobyte, Sep 2025 \- Oct 2025 · 2 mos, Remote, Delivered 3 machine learning projects — Car Price Prediction, Sales Forecasting, and Email Spam Detection — during the AICTE OIB\-SIP Internship\. Key Contributions: • Built predictive models using Python, Pandas, and Scikit\-learn with preprocessing, feature engineering, and model evaluation workflows\. • Developed Streamlit applications for interactive predictions and analytical insights\. • Collaborated remotely with mentors through regular reviews and project checkpoints to ensure timely delivery\. • Recognized as a Star Performer and awarded a Letter of Recommendation for strong project performance and execution\.

Data Science Intern at Infoz IT Solutions, Jul 2025 \- Oct 2025 · 4 mos, Secunderābād, Telangana, India, Collaborated in a team of four to develop a multimodal AI system for Telecom Customer Churn & Sentiment Analysis by integrating structured CRM data with customer feedback\. Key Contributions: • Developed an XGBoost churn prediction model \(ROC\-AUC: 96\.77%\) with SHAP explainability to identify key churn drivers\. • Built a CNN \+ BiLSTM sentiment analysis pipeline \(88% accuracy\) for automated customer feedback classification\. • Developed a Streamlit application supporting single and batch predictions with integrated analytics workflows\. • Designed a 4\-page Power BI dashboard for churn analysis, customer segmentation, and business insights\. • Processed and optimized 10K\+ customer records through scalable preprocessing, feature engineering, and inference workflows\.

## Education

Data Science Training Program, Data Science & Analytics, Teks Academy

Master of Science \(M\.Sc\.\), Computer Science, Kasturba Gandhi Degree & PG College for Women

[View the original profile](https://tal.club/meet/ayesha-7)

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