Sheryar

Data Scientist Intern

Teesside University • Tiempo completo

Jan 2026 - May 2026 • 4 mos

Developed an end-to-end machine learning pipeline to predict employee burnout risk in remote working environments, as part of a research internship. The project involved exploratory data analysis, SMOTE-based class imbalance handling, and training three classification models. Random Forest, Logistic Regression, and Gradient Boosting, alongside a Random Forest Regressor to predict continuous burnout scores. Key techniques included decision threshold tuning, five-fold cross-validation, ROC-AUC evaluation, and feature importance analysis. Gradient Boosting achieved the strongest overall performance, with Task Completion Rate identified as the most significant predictor of burnout risk across all models.

SAP ABAP Developer

TMC • Tiempo completo

Mar 2024 - Mar 2025 • 1 yr

• Developed and debugged custom SAP reports, SmartForms, and ABAP programmes to meet business-specific requirements across HCM and JVA modules. • Collaborated closely with functional consultants to translate user requirements into technical solutions, ensuring accurate data output and system reliability. • Improved structured debugging and testing practices, reducing report errors and enhancing data integrity for enterprise-scale reporting systems.

Web Developer Intern

IR Solutions • Tiempo completo

Feb 2024 - Mar 2024 • 1 mo

• Designed and maintained responsive web pages using HTML, CSS, and JavaScript to improve user experience. • Developed multiple pages of the company's official website using React.js and Next.js. • Collaborated on frontend improvements and performance optimisation across the organisation's digital presence.