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Head of Revenue Management Growth

hace 3 meses

Madrid Centro, Madrid, España Castlepark A tiempo completo

Head of Revenue Management Growth & Optimization page is loaded

Head of Revenue Management Growth & Optimization Solicitar locations Corporate Offices - Federico Mompou, Calle Federico Mompou, 5, 28050 Madrid, Madrid, Spain time type A tiempo completo posted on Publicado hace más de 30 días job requisition id JR104132

Parques Reunidos es uno de los operadores de parques de ocio más importantes y de mayor crecimiento del mundo. Con 50 años de experiencia, dispone y gestiona más de 60 parques en Europa, Norteamérica, Oriente Medio y Australia.

Actualmente estamos buscando:

Head of Revenue Management Growth & Optimization

Roles & Responsabilidades:

Roles & Responsibilities

  • Leading the Data and Business Transformation: Oversee the transformation of the RM ecosystem by providing valuable insights derived from data analysis.
  • Algorithm Development and Prototyping: Develop and prototype algorithms for analyzing company data, thereby aiding in decision-making processes.
  • Data Modeling and Visualization: Create data models and visualizations to represent complex business scenarios and data-driven insights.
  • Business Implementation of New Technology: Lead the implementation of new models AI/ML tools within the business to enhance data analysis capabilities.
  • Revenue Optimization: Work towards AI/ML optimizing revenue through strategic pricing decisions and volume control. This includes improving pricing strategies, promotions, and optimizing maximum total revenue.
  • Cross-Functional Collaboration: Collaborate with diverse teams and departments to understand business performance through insights and analytics across the company.
  • Work from scratch with unstructured raw data and efficiently develop a structured utilization of the processed data
  • Other tasks include: providing support for urgent analytic needs, collecting data and identifying the source of the data's inception. Mining and extracting valuable data from various data sources
  • The ideal candidate is highly analytical with a strong background in math and statistics. They should possess excellent critical thinking and problem-solving skills, which are essential for explaining, adapting, and anticipating business patterns and opportunities.
  • Experience in using data mining/analysis methods and tools is a must, along with a proven ability to drive business results with data-based insights. The candidate should be comfortable with data storytelling, presenting, influencing, and defending insights in English.

Requirements

Education:

  • Degree in computer science, computer engineering, Business Information Systems, Mathematics, Statistics, Information Management, or equivalent experience with Data Science.

Languages:

  • Spanish: Fluent (B2 minimum, C1 preferred)
  • English: Fluent (B2 minimum, C1 preferred)

Computer Skills:

  • Need to have experience developing software applications and a good knowledge of scripting languages for gathering and treat the data, for analyse and for visualization. Such as SQL, Python, R and Power BI

Experience:

  • Minimum of 7 years of professional experience and min 3 yrs. in related position required.
  • Experience with Alteryx and Databricks
  • Exceptional analytical and conceptual thinking skills.
  • Knowledge of data treatment, analysis and visualization tools.
  • Experience creating detailed reports and giving presentations.
  • Competency in Microsoft applications including Word, Excel, and Outlook.
  • A track record of following through on commitments.

Others:

  • Experience to develop and to implement machine learning process will be considered as a plus.
  • Experience on Agile, Scrum, Kanban.
  • Highly organized and able to multi-task and prioritize effectively.
  • Excellent verbal, written, listening, and interpersonal skills.
  • Knowledge of programming languages.
  • Effective Communication: Carefully listening to management, data analysts and relevant staff to come up with the best data design; explaining complex concepts to non-technical colleagues.
  • Good experience with, or a good understanding of, Data Analysis best practices

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