Data Analyst in Business Research
Budget: ₹150,000 – ₹250,000 INR
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.