Senior Lifestyle Revenue Manager – Hybrid (London)

PPHE Hotel Group; Greater London; Hybrid; GBP 60,000 - GBP 80,000; Full time

Job summary

A leading hotel management company is seeking a Senior Lifestyle Revenue Manager at their London Head Office. This role involves developing revenue strategies that reflect the unique identity of lifestyle hotels, driving commercial performance, and enhancing team capabilities. The ideal candidate will have over 3 years of Revenue Management experience, understanding of lifestyle trends, and a passion for innovative strategies. This position offers a dynamic environment where creative contributions are valued and AI-driven approaches are explored.

Benefits

Up to 20% bonus based on KPI’s

Up to 2 days per week from home

Private healthcare option

Company pension plan

Access to 40% of pay before payday

Discounted rates at various retailers

30 days holiday plus bank holidays

Recommend a friend scheme

Free dry cleaning for workwear

Annual staff parties and events

Qualifications

• At least 3 years of Revenue Management experience.
• Background in Hospitality or Retail.
• Familiarity with AI-driven approaches.

Responsibilities

• Curate revenue strategies based on guest behaviours and cultural trends.
• Drive commercial performance across revenue streams.
• Lead and empower the Revenue Manager.

Skills

Revenue Management experience

Understanding of lifestyle trends

Confident communication

Analytical mindset

Leadership and coaching

Tech-savviness

Job description

A leading hotel management company is seeking a Senior Lifestyle Revenue Manager at their London Head Office. This role involves developing revenue strategies that reflect the unique identity of lifestyle hotels, driving commercial performance, and enhancing team capabilities. The ideal candidate will have over 3 years of Revenue Management experience, understanding of lifestyle trends, and a passion for innovative strategies. This position offers a dynamic environment where creative contributions are valued and AI-driven approaches are explored.