Muhammad Awan

MSc graduate in Artificial Intelligence and Data Science from the University of Hull, with hands-on experience developing machine learning models, time-series forecasting systems, and data pipelines. Skilled in transforming raw data into actionable insights using Python, SQL, NoSQL databases, data visualization, and machine learning frameworks. Experienced in working with cloud-based environments and Linux systems, contributing to end-to-end data workflows from data ingestion and pre-processing to model development and evaluation, with a strong focus on scalable, data-driven solutions.

Business Analyst/QA at WeatherWalay (2022-11 – 2024-08)

Led business analysis for GSMA-funded agricultural early warning systems and engineered scalable ETL pipelines for real-time weather data processing.

• Led business analysis for GSMA-funded agricultural early warning systems, increasing farmer outreach by 20% through data-driven solutions.
• Engineered scalable ETL pipelines to extract, transform, and load data from APIs, files, surveys, and relational/non-relational databases, boosting real-time weather data accuracy by 30% for national forecasting applications.
• Crafted interactive Power BI dashboards and Excel reports to visualize complex datasets, enhancing data-driven decision-making for stakeholders.
• Designed and documented comprehensive system and workflow diagrams using draw.io and Figma, improving transparency and collaboration among interdisciplinary teams.
• Spearheaded feature enhancement initiatives by leveraging data analytics to identify and resolve over 20 critical defects, increasing overall product quality by 20%.
• Streamlined defect triaging and resolution processes, reducing bug turnaround time on ARM portals by 50% through efficient cross-team coordination, improving system uptime and data pipeline robustness.

Software Test Engineer - Intern at Arkhitech (2022-08 – 2022-11)

Defined and executed test cases and organized API testing using Postman, reducing manual testing time and improving defect detection.

• Defined and executed 100+ test cases and Organised API testing using Postman, reducing manual testing time by 30% and improving defect detection.
• Documented and tracked 50+ bugs through full resolution with a 95% fix verification rate, collaborating closely with developers to enhance test coverage and software quality.
• Maintained comprehensive test documentation and applied both manual and automated QA methodologies following industry best practices to ensure software reliability

MSc in Artificial Intelligence and Data Science – University of Hull (2024-09 – 2025-09)

Bachelor's in Software Engineering – Riphah International University (2018-09 – 2022-07)