Market Research Data Analyst
New
B
Baymard InstituteEcommerce UX
This is a remote, full-time position from the UK, Ireland, or the EU.Full-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- We expect you to be fully proficient in written English.
- Experience
- 2–3+ years of professional experience in quantitative research, market research, survey research, consumer insights, or a closely related field.
- Required Skills
- Microsoft ExcelGoogle SheetsMarket Research
Requirements
- Have 2–3+ years of professional experience in quantitative research, market research, survey research, consumer insights, or a closely related field.
- Have hands-on experience designing questionnaires and conducting online survey research.
- Have experience analyzing survey datasets and synthesizing quantitative findings into meaningful conclusions.
- Understand survey-design fundamentals, including question wording, response scales, questionnaire structure, screening, and common sources of bias.
- Have experience with survey platforms such as Alchemer, Qualtrics, SurveyMonkey, or similar.
- Have experience using Excel, Google Sheets, statistical software, or other analytical tools to explore and analyze quantitative data.
- Be comfortable interpreting percentages, distributions, cross-tabulations, and differences between respondent groups.
- Be able to communicate findings clearly in writing to audiences without a research background.
- Be fully proficient in written English.
Responsibilities
- Research industries, consumers, and ecommerce experiences to investigate.
- Translate research objectives into clear, testable research questions.
- Design questionnaires, including wording, response scales, structure, branching, and screening criteria.
- Identify appropriate respondent audiences, quotas, and sample requirements.
- Program and QA surveys using Alchemer, including logic, quotas, branching, and redirects.
- Coordinate with sample providers on feasibility, targeting, and setup.
- Monitor fieldwork and assess incoming responses for data-quality issues.
- Clean, structure, and analyze survey datasets, including comparisons across questions and respondent segments.
- Create charts and synthesize findings into concise, evidence-based insights.
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