Own the analytical foundation for a multi-site labour optimisation programme. Analyze labour productivity, identify and size efficiency opportunities, improve reporting, support demand-to-labour modeling, evaluate forecast accuracy, and measure scheduling changes. Partner with Operations, Finance, Data Science, Business Partners, and General Managers to implement improvements while protecting member experience. The role requires advanced SQL, financial modeling, BI development, and experience with workforce, payroll, scheduling, and operational data.
The Role..
We are starting a labour optimisation programme with our Operations team, alongside FP&A and Data Science. The aim is to improve our wage percentage to sales while improving service standards at the same time. We are not interested in an approach that delivers one at the expense of the other.
We are currently selecting an advanced scheduling platform to support this. The analytical foundation underneath it — how we measure productivity, what our labour standards are, how good our demand forecasts need to be — is what this role owns.
You will sit in the Data team and work in close partnership with FP&A. Analysis alone will not move the number; changes stick when a Finance Business Partner and a General Manager can see the opportunity in their own House, agree the size of it and hold it in their forecast. Your job is to give them that, in a form they can act on.
Key responsibilities..
- Labour productivity analysis, identifying site-by-site opportunities for efficiency gains and sizing each one
- Work with Operations and Finance to trial changes to scheduling and measure their impact
- Build improved labour reporting, so Business Partners and GMs can see productivity, schedule changes and shift adherence on a daily and weekly cadence
- Support Finance translate demand forecasts into labour requirements, helping to build the models that turn covers, check-ins, treatments and occupancy into hours by role
- Partner with our Data Science and Operations teams to understand forecast accuracy and recommend improvements
- Connect labour deployment to member experience, so that productivity gains are demonstrably not coming out of the House
Required skills and experience
- Proven experience in labour optimisation. You have personally delivered measurable improvement in wage percentage or sales per labour hour in a multi-site operation, and can talk us through the levers you pulled, how you sized them and how you proved the result
- A track record of partnering finance and operational stakeholders to land change, not just report on it
- 5+ years in an analytics role, with genuine multi-site operational exposure — hospitality, retail, leisure or QSR
- Advanced SQL, and comfort in a modelled data warehouse (Snowflake and dbt an advantage)
- Strong financial modelling in Excel, and fluency in P&L mechanics — wage percentage, flow-through, contribution
- BI development experience (Omni, Looker, Tableau or Power BI), building tools operators actually use
- Experience with rota, time and attendance and payroll data, and a realistic view of its challenges
- Able to evaluate a demand forecast critically — accuracy, bias, seasonality — without needing to build one
Desirable
- Experience with a workforce management or scheduling platform — Unifocus, HotSchedules, Dayforce, Fourth, S4 Labour, UKG, Quinyx or similar
- An understanding of how labour regulation constrains labour models internationally, particularly the US — predictive scheduling and fair workweek rules, overtime and break requirements
- Labour standards or time-and-motion experience
- Python for analysis, or use of AI tooling such as Claude Code to accelerate it
- Experience linking labour deployment to customer experience outcomes
Soho House & Co London, England Office
London, United Kingdom
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