Quantitative Research Data Analyst

Description

We are looking for a Research Data Analyst to lead the technical validation and integration of AI-augmented samples into classic survey datasets. You’ll work at the forefront of AI transformation for market research, helping top-tier brands and agencies make sense of the future of sampling. From regression models to advanced quality control, your work will be instrumental in bridging the gap between traditional and AI-powered, hybrid, quantitative research.

What makes this project exciting?

This platform harnesses generative AI and synthetic data to elevate the field of market research. It brings unique tools that improve data reliability for hard-to-reach or underrepresented groups and efficiently identify fraudulent survey responses. The platform empowers research teams to modernize data collection by generating synthetic samples and automating report creation, allowing for deeper, more granular insights into fields like consumer behavior and political trends. Its innovative approach showcases the transformative potential of AI to enhance data quality and accuracy, making data-driven research faster, more reliable, and more inclusive.

What makes you a great fit

• 3+ years of experience in quantitative research, preferably in an agency, insights team, or analytics role.
• Deep understanding of questionnaire logic, survey flow, and data cleaning/processing.
• Proven track record in advanced statistical analysis of survey data.
• Strong eye for data quality and integrity, with experience identifying suspicious patterns or poor-quality responses.
• Fluent in written and spoken English — you’ll be speaking directly with clients.
• Excellent communicator, capable of creating impactful narratives from data.
• Bonus: familiarity with R, Python, or survey platforms (like Decipher, Qualtrics, Confirmit).

Your day-to-day in this position

• Lead the technical analysis and validation of augmented synthetic samples vs. traditionally collected samples.
• Support the implementation and integration of AI-generated respondents into real-world quantitative studies.
• Review questionnaires and survey structure, advising on logic and data processing best practices.
• Detect and flag data quality issues, including fraudulent or inconsistent responses.
• Conduct advanced analyses using tools such as: Regression models (linear, logistic), Driver analysis, MaxDiff and TURF, Conjoint analysis (CBC, ACBC), Segmentation and clustering, Factor and principal component analysis, Significance testing (t-tests, ANOVA, chi-square).
• Translate complex results into simple, compelling stories for internal stakeholders and client presentations.
• Collaborate closely with product, data science, and customer-facing teams to ensure the scientific robustness of Fairgen’s solutions.
• Present findings to clients — in writing, in person, or via Zoom — in clear, confident, and fluent English.

Why work with us?

• People-oriented management without bureaucracy
• The friendly climate inside the company is confirmed by the frequent comeback of previous employees
• Flexible working schedule
• 29 paid time off (18 working days per year, plus 11 days — all national holidays)
• 10 sick leave days
• Full financial and legal support for private entrepreneurs
• Free English classes with native speakers or with Ukrainian teachers (for your choice)
• Dedicated HR

Our next steps

✅ Intro call with a Recruiter — ✅ Client intro interview — ✅ Tech interview — ✅ Final client interview — ✅ Offer