Revenue Intelligence Principal Research Scientist

The Principal Research Scientist owns the empirical integrity of QNT/L's research system. They design and strengthen the methodologies behind QNT/L Research, test the firm's commercial hypotheses against evidence, establish quantitative standards, and ensure that published claims can withstand scrutiny from executives, investors, researchers, and sophisticated institutional buyers.

• Design rigorous quantitative and mixed-method research programs around B2B commercial systems, organizational performance, revenue operations, buyer behavior, sales productivity, leadership, and AI
• Develop research methodologies, sampling frameworks, survey instruments, longitudinal studies, benchmark construction, statistical analyses, and validation protocols
• Review QNT/L frameworks and hypotheses for methodological soundness
• Distinguish clearly between observed evidence, inference, correlation, causation, interpretation, and projection
• Own or materially influence QNT/L's research standards, claims validation, citation discipline, provenance, and reproducibility
• Build datasets capable of testing constructs such as Motion Integrity, Signal Debt, Pipeline Fiction, and Executive Continuity
• Establish validation frameworks for the Revenue Architecture Index before any predictive claims are made
• Analyze data produced through Revenue Architecture Diagnostics while maintaining client confidentiality and aggregation standards
• Identify when QNT/L's evidence does not support its thesis, with explicit authority to say so
• Translate sophisticated empirical work into conclusions that CEOs, boards, PE operating partners, and investors can understand, without compromising methodological integrity
• Contribute to major QNT/L research publications and methodology papers
• Help determine which questions are worthy of becoming formal QNT/L research programs

• 10+ years in applied research, economics, organizational science, quantitative business research, behavioral science, industrial-organizational psychology, management science, or a closely related discipline
• Demonstrated experience designing and executing original empirical research, not merely synthesizing third-party research
• Strong command of statistical inference, research design, survey methodology, and sampling
• Fluency in regression and multivariate analysis, longitudinal analysis, and causal inference principles
• Depth in measurement and construct validity, experimental and quasi-experimental design, data quality and bias, and reproducible research
• Published research, substantial institutional research reports, or comparable evidence of serious methodological work
• Experience working with large or messy real-world datasets
• Ability to challenge senior executives intellectually without becoming academic for academia's sake
• Comfort saying, "The evidence does not support that conclusion"

• Former Gartner, Forrester, or Sirius Decisions senior researcher or analyst
• Research leadership from Gallup, Korn Ferry, Mercer, or a serious economics or workforce research institution
• Applied researcher from McKinsey Global Institute, Bain, BCG, or another genuinely empirical research organization
• PhD-level researcher in economics, organizational behavior, industrial-organizational psychology, management science, statistics, behavioral science, or a related quantitative field
• The strongest profile is a hybrid:
  PhD-level methodological sophistication, 10 to 15 years of applied commercial research, and enough business experience to keep QNT/L from becoming an academic journal

You will not produce content that dresses up conclusions the data cannot carry. Your mandate is the opposite: hold QNT/L's thinking to a standard that survives executives, investors, and sophisticated institutional buyers. You will have explicit authority to say the evidence does not support the thesis, and that authority is the point. This is research that decides what the firm is willing to claim.