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
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Design and execute system-level and UX research studies to evaluate product performance and user experience.
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Analyze quantitative and qualitative data to identify anomalies, validate workflows, and improve test procedures.
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Develop Python-based tools to automate data processing, validation, and reporting workflows.
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Synthesize research findings into actionable recommendations for engineering and product teams.
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Collaborate with cross-functional partners to refine testing strategies and research methodology.
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Perform manual and automated QA, regression testing, and bug tracking to ensure reliable outcomes.
Qualifications
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B.S. in Cognitive Science with specialization in Machine Learning and Neural Computation (UC San Diego).
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Experience in system validation, power data analysis, and structured research from technical specifications.
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UX research experience with prototype usability studies and data quality verification.
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Strong foundation in research design, data analysis, and statistical interpretation.
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Proficient in Python for automation, data processing, and workflow optimization.
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Coursework in Data Science, Machine Learning, Business Analytics, and Cognitive Development.
Relevant Experience Areas
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System-level RF validation and analysis
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UX research and usability testing
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Data consistency checks and anomaly detection
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Automation of data parsing and classification
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Cross-functional reporting and stakeholder communication
