Systems & UX Research Engineer in VERVIERS at WFNQASD5

Summary

Research-oriented Cognitive Science graduate specializing in machine learning, data-driven insight generation, and UX validation. Proven experience conducting structured studies, analyzing system performance data, and translating findings into product and workflow improvements. Strong cross-functional collaborator with hands-on experience in usability research, QA validation, and Python-based automation.

Responsibilities

• Design and execute system-level and UX research studies to evaluate product performance and user experience.
• Analyze quantitative and qualitative data to identify anomalies, validate workflows, and improve test procedures.
• Develop Python-based tools to automate data processing, validation, and reporting workflows.
• Synthesize research findings into actionable recommendations for engineering and product teams.
• Collaborate with cross-functional partners to refine testing strategies and research methodology.
• Perform manual and automated QA, regression testing, and bug tracking to ensure reliable outcomes.

Qualifications

• B.S. in Cognitive Science with specialization in Machine Learning and Neural Computation (UC San Diego).
• Experience in system validation, power data analysis, and structured research from technical specifications.
• UX research experience with prototype usability studies and data quality verification.
• Strong foundation in research design, data analysis, and statistical interpretation.
• Proficient in Python for automation, data processing, and workflow optimization.
• Coursework in Data Science, Machine Learning, Business Analytics, and Cognitive Development.

Relevant Experience Areas

• System-level RF validation and analysis
• UX research and usability testing
• Data consistency checks and anomaly detection
• Automation of data parsing and classification
• Cross-functional reporting and stakeholder communication