Sr Director Revenue Optimization & Modeling

Hertz•Atlanta, GA

20h•$200,000

About The Position

We are seeking a strategic and results-driven Senior Director of Revenue Optimization and Modelling to lead our revenue generation initiatives with the car rental industry. The ideal candidate will have a deep expertise in the travel industry and be able to adapt the current methods of demand forecasting and revenue generation to the next generation of revenue management. This position will partner with stakeholders such as Fleet, Sales/Distribution, Product and Technology to design, develop, and maintain advanced analytical model and tools to be used in the day to day decision making process for revenue generation.

Requirements

Masters’s degree in highly quantitative field (Applied Mathematics, Operational Research, Probability and Statistics, etc.) or equivalent work experience required
Minimum 10+ years’ experience in data analytics, ML fundamentals such as Linear regression, Decision trees & Random Forest. K-means, etc required.
5+ years’ experience leading a data, modeling or analytics team required
Proficiency in Python, R, Familiarity C++; and Java.
Experience working in cloud platforms, (AWS, Google, Azure)
Expertise in large data, (NoSql, Hadoop, Spark, etc.)
Strong critical thinking and problem-solving skills with ability to translate business problems into data driven solutions
Experience communicating and presenting models and findings to senior leaders and non-technical management

Nice To Haves

Knowledge of Car, Hotel, and/or Airline industry a plus

Responsibilities

Innovation: Develop modeling techniques that support the overall enterprise strategy. Execution of those methods is fundamental to be successful in this role.
Strategic Development: Develop and oversee large scale R&D efforts in revenue forecasting that align to corporate goals
Vendor Management: Select and manage a variety of vendors in terms of scope, synergy and coordination in conjunction with internal IT teams
Customer Insights: Modify existing models and processes to be customer centric instead of operationally focused. Determine customer segmentation and willingness to pay coefficients.
Market Analytics: Analyze market trends, competitor pricing and consumer demand to inform growth strategies
Adoption: Deployment of predictive and prescriptive analytics and adoption of new tools and technologies
Leadership: Lead a team of 5+ data scientist and data engineers to clean, preprocess and model data.
Collaboration: Build and maintain cross-functional relationships with Revenue Management, Product teams, Sales/Distribution and Technology