Consultant - Quantitative Research Specialist/Pricing Research Analyst

About MojoTech MojoTech is an innovative technology consulting firm that leverages strategy, design, data, and software engineering to create results-driven, AI-enabled, digital products and experiences. We partner with our clients to discover and build tomorrow’s intelligent innovations, empowering every company to unlock future market potential, maximize returns on innovation, and drive transformational change. About the Role MojoTech is hiring a Quantitative Research Specialist/Pricing Research Analyst as a contractor to lead willingness-to-pay research for AI product strategy assessments across a private equity portfolio. This role owns evidence-gathering: designing and running the structured pricing studies, including sourcing and surveying non-customers, that validate whether a net-new AI opportunity has real commercial pull beyond what qualitative signals alone can show. Duration: 6-8 weeks. What You'll Do Design conjoint and Van Westendorp studies matched to the specific opportunity being tested Design and conduct any supporting interviews needed to properly scope or validate a study Source and recruit survey respondents who match the target buyer, including non-customers, using the right tools and channels to reach people who aren't already in a company's customer base Leverage existing panel provider relationships and purpose-built pricing/choice research tools to stand up studies quickly Use AI tools to accelerate study design and analysis, while critically checking that output for errors before it's used Run the statistical analysis: conjoint utility calculations, Van Westendorp price-sensitivity curves Interpret and caveat results correctly for a non-technical audience, and hand off findings the AI Strategist can incorporate into ranked opportunity lists What You'll Bring Demonstrated expertise running willingness-to-pay studies (conjoint, Van Westendorp), with a track record across multiple studies, ideally in B2B/SaaS or comparable contexts, including sample size and panel design competence Proven experience designing and conducting both surveys and interviews as part of a research study Hands-on experience sourcing and recruiting non-customer survey populations for a specific target buyer profile, not just convenience samples or theoretical familiarity Working knowledge of the specific tools, platforms, and channels used to recruit non-customer respondents Existing relationships with panel providers and fluency with survey platforms purpose-built for pricing and choice-modeling research Ability to use AI tools to augment study design and analysis, paired with the judgment to critically evaluate that output Strong applied statistics: sample size determination, choice-modeling math, correct interpretation of results Clear written communication of quantitative findings for a non-technical, executive audience Nice to Have Experience conducting these studies for private equity portfolio companies Domain familiarity with healthcare IT, life sciences, RegTech/compliance, financial services, or other regulated B2B software markets What Success Looks Like Your studies use respondent populations that genuinely test unmet need, including real non-customers, not just existing customer bias. Your panel and tooling relationships let a study stand up fast within engagement timelines. Your analysis is statistically sound and defensible enough to support a commercial go/no-go call on a net-new AI opportunity.