Business Researcher
Budget: $250 – $750 USD
Required Skills and Proficiency:
• Experience defining and operationalizing North Star metrics, OKRs, and outcome-driven roadmaps.
• Strong understanding of causal inference, DAGs, and Bayesian frameworks for decision-making.
• Proficiency in A/B testing, quasi-experimental methods, and Bayesian statistics.
• Skilled in data modelling, telemetry integration, and survival/real options analysis for portfolio decisions.
• Ability to design and evaluate experimentation cultures that accelerate product velocity.
• Hands-on experience with LLMs, natural language processing, and thematic analysis of unstructured data, knowledge of responsible AI practices, ethical feature development, and AI-assisted product workflows.
• Familiarity with “PRD as Code” approaches and automation in product specifications.
• Knowledge of dual-track agile, discovery practices at scale, and modern operating models for enterprises.
• Familiarity with platform vs. feature team trade-offs and organizational transformation patterns.
• Experience translating support data, accessibility needs, and localization requirements into product improvements.
• Familiarity with GDPR, PCI, and privacy-by-design frameworks for compliant product development.
• Ability to develop ethical and economic frameworks for feature decommissioning and sunsetting.
• Prior academic research, writing and publishing experience
To apply:
Share your prior research works, such as Google Scholar or ORCID.
• Experience defining and operationalizing North Star metrics, OKRs, and outcome-driven roadmaps.
• Strong understanding of causal inference, DAGs, and Bayesian frameworks for decision-making.
• Proficiency in A/B testing, quasi-experimental methods, and Bayesian statistics.
• Skilled in data modelling, telemetry integration, and survival/real options analysis for portfolio decisions.
• Ability to design and evaluate experimentation cultures that accelerate product velocity.
• Hands-on experience with LLMs, natural language processing, and thematic analysis of unstructured data, knowledge of responsible AI practices, ethical feature development, and AI-assisted product workflows.
• Familiarity with “PRD as Code” approaches and automation in product specifications.
• Knowledge of dual-track agile, discovery practices at scale, and modern operating models for enterprises.
• Familiarity with platform vs. feature team trade-offs and organizational transformation patterns.
• Experience translating support data, accessibility needs, and localization requirements into product improvements.
• Familiarity with GDPR, PCI, and privacy-by-design frameworks for compliant product development.
• Ability to develop ethical and economic frameworks for feature decommissioning and sunsetting.
• Prior academic research, writing and publishing experience
To apply:
Share your prior research works, such as Google Scholar or ORCID.