Data Scientist Senior Manager

Department: Revenue & Reservations

Location: United Arab Emirates - Dubai

Description
About Kempinski:
At Kempinski, we don't just offer stays; we curate moments. As a hospitality organization, anchored in a legacy of elegance and a pioneering spirit, we have grown into a collection of iconic hotels and resorts around the world, each a landmark in its own right. From grand palaces steeped in history to contemporary masterpieces of design, Kempinski is where impeccable service meets authentic local experiences.
We empower our people to be artisans of hospitality, fostering an environment where passion is nurtured, individuality is celebrated, and every detail is thoughtfully considered. Joining Kempinski means becoming part of a family that is dedicated to creating memories that last a lifetime for our guests, and a fulfilling and enriching career for our team.
If you are driven by excellence, inspired by the art of hospitality, and seek to contribute to a legacy of luxury, we invite you to explore the exceptional opportunities that await you at Kempinski Hotels. Come, be a part of our story.
Key Responsibilities
• Data Strategy & Infrastructure
o Collaborate with IT teams to enhance data pipelines, governance, and infrastructure for advanced analytics tools, initially focused on revenue management.
o Design and oversee the development of Revenue Management Tools and data infrastructure, overseeing multiple providers.
o Define and enforce data standards, quality measures and reporting consistency across commercial organization, including the identification of new data streams that would augment the quality of algorithms and modelling.
o Ensure the quality, integrity, and accessibility of key data sources relevant to all Commercial organization, supporting the team in data availability.
o Champion a data-driven culture across all business units, working closely with cross-functional teams (strategy, finance, operations, digital) to align analytics with strategic objectives.
o Serve as an internal thought leader on emerging trends, tools and applications of data science in the travel and leisure sector.
o Build a high-performing data science team (year 2 onwards)
• Revenue Management Strategy
o Partner with commercial teams to develop data-driven tools for forecasting, pricing, product mix, inventory and channel optimization.
o Support dynamic pricing and demand management initiatives through data automation and real-time analytics.
o Develop algorithms to enhance channel mix, distribution strategy, and profitability. o Build recommendation engines for upselling, cross-selling, and dynamic packaging.
o Scale up the tools across the organization.
o Contribute to widespread adoption of implemented tools by ensuring proper understanding of functionality and business logics by end users, capturing feedback and enhancement suggestions from user community that can be prioritized and packaged in future releases.
Skills, Knowledge and Expertise

Looking to get Placed? Try our Placement Guarantee Plan

Get Hired
• Education and Functional Competency

o 3-5 years of experience in data science, advanced analytics, or quantitative consulting o Strong expertise in big data-platforms, data analytics and engineering, predictive modelling.
o Track record of driving measurable commercial and operational impact through data science.
o Proven track record in revenue management or demand forecasting is a strong plus.
o Bachelor's or master's degree in Data Science, Computer Science, Statistics, Economics, or a related quantitative discipline

• Key Competencies and Personality

o Strong analytical and quantitative reasoning capabilities.
o Proficiency in building and deploying analytical models, using modern data tools and programming techniques.
o Ability to effectively communicate, explain and educate on complex models across different business units and management layers.
o Ability to work with large and complex datasets to derive actionable insights.
o Familiarity with contemporary data science methods and approaches to automation, modelling, and visualization.
o Programming: Python, SQL o Cloud / Data Engineering: AWS (S3), Azure, Databricks o Visualization / BI: Power BI, Tableau