Senior Data Analyst – Labour & Productivity (Contractor)

Sohohouseco; Greater London; Sur place; GBP 70 000 - 100 000; Plein temps

Résumé du poste

Soho House Co. is launching a labour optimisation programme within its Operations, FP&A and Data Science teams. The analytical foundation behind productivity, labour standards and forecast requirements is owned by this role.

You will be part of the Data team working with Finance Business Partners and General Managers to translate opportunities into forecasted actions and measurable gains. Strong SQL, Excel modelling and BI skills are essential.

Qualifications

• Proven experience in labour optimisation with measurable improvements.
• Track record of partnering finance and operations to land change.
• 5+ years in an analytics role with multi-site exposure.

Responsabilités

• Labour productivity analysis and sizing opportunities across sites.
• Collaborate with Operations and Finance to trial scheduling changes and measure impact.
• Build labour reporting for daily/weekly visibility to Business Partners and GMs.
• Translate demand forecasts into labour requirements and hours by role.
• Partner with Data Science and Operations to assess forecast accuracy and propose improvements.
• Link labour deployment to member experience, ensuring productivity gains don’t harm the House.

Connaissances

Labour optimisation

Stakeholder collaboration

Analytics (multi-site)

SQL

Data warehouse modelling

Financial modelling in Excel

BI tools

Rota/attendance/payroll data

Forecast evaluation

Workforce scheduling platforms

Python / AI tooling

Outils

Snowflake

dbt

Description du poste

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