Jr Quantitative Ux Researcher

Summary

Join Skydropx's dynamic and multicultural team as a Quantitative Researcher! You will define and execute quantitative research objectives, design and manage surveys, analyze data using tools like Excel, R, SQL, and Python, conduct A/B testing, and establish key performance indicators (KPIs). Collaborate with qualitative researchers and create insightful reports and visualizations. Identify user segments, evaluate large-scale usability, and validate design hypotheses. Continuous product monitoring using data analysis and tracking tools is also crucial. This role requires proven performance in a current position, at least 6 months of company tenure, and intermediate/advanced skills in Excel, SQL, and BigQuery.

Requirements

• Satisfactory performance and description compliance in the current position (A and B)
• Minimum seniority of 6 months in the company
• Intermediate/advanced handling of Excel, SQL, and BigQuery

Responsibilities

• Define quantitative research objectives: Collaborate with the product design team to establish key questions that will guide the research and define the relevant metrics to evaluate the user experience
• Design and administer quantitative surveys and studies: Create structured surveys, forms, and other methods to collect quantitative data
• Analyze quantitative data: Use statistical tools and data analysis software (such as Excel, R, SQL, or Python) to interpret large volumes of information, identify patterns and trends in user behavior
• A/B testing and controlled experiments: Design, execute, and analyze A/B experiments to measure the impact of different changes in the user experience or user interface
• Establish key metrics (KPIs): Define and implement key performance indicators (KPIs) that measure the effectiveness of products and services from the user's perspective
• Collaborate with qualitative researchers: Integrate the findings of qualitative and quantitative research to provide a comprehensive view of the user experience
• Create reports and data visualizations: Translate complex data into clear reports and presentations, using graphs, tables, and dashboards that are understandable to non-technical stakeholders
• Identification of user segments: Use statistical techniques (such as cluster analysis or segmentation) to identify different groups of users with similar behaviors
• Evaluation of large-scale usability: Perform usability analysis using metrics such as task time, error rates, and user satisfaction in large groups
• Validation of design hypotheses: Validate design concepts or new functionalities through quantitative studies, ensuring that the data supports or refutes their effectiveness
• Continuous product monitoring: Configure and monitor product performance over time using data analysis, tracking tools, and real-time user experience evaluation