Research Lead

Reejig is the Work Operating System for the AI powered enterprise.

We give companies a complete, validated view of their work by mapping every role, task, skill, and workflow. With this intelligence, we redesign how work should flow, surface where automation creates the highest leverage, and recommend the right AI agents for the enterprise.

Every change is measured and tied to real operational and workforce impact.

Inside Reejig, we build the same future we sell. We are developing our own AI powered workforce that supports our teams and our customers.

This is a place for builders who want to help define how work will operate in the AI era.

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.