As a Data Analyst at InterContinental Hotels & Resorts, you will support business decision-making by extracting, analyzing, and interpreting data from hotel systems and business platforms. You’ll develop insights that help optimize hotel operations, drive revenue performance, improve guest experience, and support cross-functional initiatives across departments such as Operations, Revenue, Sales & Marketing.

Key Responsibilities:

• Data Extraction & Preparation
  • Collect, clean, validate, and transform data from multiple hotel systems and databases (e.g., PMS, revenue systems) using SQL
• Analysis & Modeling
  • Perform statistical analysis, predictive modeling, and forecasting using tools such as IBM SPSS, Excel, or other analytics platforms.
• Reporting & Dashboards
  • Develop and maintain dashboards, scorecards, and KPI trackers to monitor performance and trends.
• Insights & Recommendations
  • Generate actionable insights and business recommendations through structured analysis and storytelling.
• Cross-Functional Support
  • Collaborate with hotel operations, marketing, revenue management, and commercial teams to support analytics needs and improve data processes.
• Presentations
  • Present findings clearly and effectively to stakeholders, both verbally and via written reports.

Required Skills & Qualifications:

• Education:Bachelor’s degree in Business Analytics, Statistics, Data Science, Computer Science, Mathematics, Economics, or related field.
• Technical Skills:
  • Strong SQL skills for querying and manipulating large datasets.
  • Experience with IBM SPSS for statistical analysis
  • Advanced Microsoft Excel (pivot tables, formulas).
  • Familiarity with BI tools (e.g., Tableau, Power BI) is a plus.
• Soft Skills:
  • Excellent analytical and problem-solving skills.
  • Strong communication and presentation abilities.
  • Attention to detail and ability to meet deadlines.
  • Ability to work collaboratively across teams.

Preferred / Nice-to-Have:

• Experience in hospitality analytics is advantageous
• Prior exposure to predictive analytics, forecasting, or advanced statistical techniques.
• Certification in analytics tools (e.g., SPSS).