Research Lead

Role Overview: We are looking for a Research Lead to shape the thinking and methodology behind some of Reejig's most important workforce insights. Reejig helps organisations understand how work is changing in the AI era: how roles and tasks are evolving, where technology can create capacity, and what that means for workforce decisions. This role sits at the centre of that work, turning deep workforce expertise into rigorous models, measures and product experiences that customers can trust. You will combine domain knowledge with hands-on analytical skills. You should be comfortable moving from a workforce question to a model, testing whether it holds up, and explaining the answer clearly to both technical teams and senior enterprise leaders.

What You Will Do: Own and evolve the research methodologies that power workforce, work-design and AI-related insights across the product Develop practical models for translating task- and role-level signals into meaningful measures of capacity, cost and impact Use external research, occupational data and customer evidence to validate and improve our methods over time Build evaluation approaches that help us measure the quality and consistency of AI-generated outputs Shape how roles, tasks, skills, seniority and other workforce concepts are represented so the product remains coherent as it grows Improve the quality and consistency of skills and workforce taxonomies across customer environments Work with LLMs and structured prompting as part of the research and product-development process, with a strong focus on evaluation and reliability Turn complex methodology into clear, credible explanations for customers, Customer Success and go-to-market teams Partner closely with product and engineering to take new research from idea to production safely and measurably What You Need To Be Effective You will thrive here if you have spent years thinking deeply about how work is structured, how roles change, and how organisations make workforce decisions. You should also enjoy getting close to the data yourself rather than stopping at a conceptual framework. What We Value Deep expertise in workforce planning, job architecture, skills, organisational design or a related field Strong quantitative judgment and the curiosity to investigate when a result does not look right Rigour about evidence, assumptions and uncertainty Practical experience using LLMs, paired with a healthy instinct to test rather than simply trust their outputs Clear writing and communication that can make a complex methodology understandable without oversimplifying it Comfort making thoughtful judgment calls when the data cannot fully settle a question A builder mindset: you enjoy turning ideas into working models, evaluations and product capabilities

What Success Looks Like: Reejig's most important workforce insights are well-defined, measurable and trusted by customers New methodologies are tested and improved before they are broadly introduced Evaluation catches quality regressions early and helps the product improve over time Customers can understand the reasoning behind the insights they use to make decisions Product, engineering and customer teams have a shared and consistent language for how the models work Strong alignment with The Reejig Code

Minimum Requirements: 6+ years in workforce analytics, people analytics, workforce planning, job architecture, skills or a closely related field Hands-on proficiency with SQL and either Python or R Experience designing metrics, scoring approaches, analytical frameworks or models and explaining the assumptions behind them Experience validating analytical outputs against benchmarks, expert judgment or labelled data Working knowledge of occupational or skills frameworks such as O*NET, ESCO or similar Familiarity with LLM evaluation approaches and the strengths and limitations of AI-generated outputs Strong written communication for both technical and executive audiences

Nice to have: Background in labour economics, industrial-organisational psychology or a quantitative social science Familiarity with research on task change, automation or AI's impact on work Experience with prompt engineering, evaluation tooling or structured AI workflows Experience with skills taxonomies, ontologies or knowledge graphs at enterprise scale Why This Matters The workforce is changing quickly, and organisations need more than broad predictions about AI. They need clear, defensible ways to understand what is changing inside their own workforce and what to do next. This role has the opportunity to set that standard at Reejig and influence how some of the world's largest organisations make those decisions.