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