Under general direction of the, Senior Yield Management Manager, develops and implements programs and pricing and yield management strategies using advanced data science techniques to maximize revenue. Advanced data science techniques include machine learning, neural networks, time series economic forecasting, prescriptive and predictive analytics, marketing analytics, advanced SQL querying using unstructured and structured data, and creative entrepreneurial projects, including pricing products strategies, that use other artificial intelligence and economics techniques.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
strategy for revenue maximization and ancillary revenue generation.
Apply statistical analysis, pattern recognition, and machine learning to identify the economic plan and strategy for revenue maximization and ancillary revenue generation.
- Utilizes advanced statistical software, like R or Python, to perform economic time series analysis, predictive analytics, prescriptive analytics, and other artificial intelligence techniques
- Apply relevant yield management demand forecasting techniques and develop/implement optimization algorithms to maximize revenue across all parking
- Understand and measure consumer behavior to create pricing strategies and price points that appeal to different customer segments and maximize This includes utilizing machine learning segmentation techniques like K-Means clustering and price elasticity testing to maximize revenue to the right customer for the right price
- Identify issues in data or the marketplace, diagnose root cause and be able to create a strategy to implement a
- Demonstrate advanced technical skills to build reports, incorporate automation, develop forecasts, manage databases and interface with the IT This includes working with unstructured data using advanced SQL skills.
- Develop strategic and operational revenue plans for the airport's various parking products, measure the key metrics and then communicate results in written, visual or verbal format throughout all levels of the organization, primarily the C-suite.
- Create and manage econometric models to predict future revenue, optimal prices, churn, digital marketing strategies, segmentation, optimal inventory, occupancy, and optimal product marketing mixes
- Create and manage workflows for Data Science Studio to create machine learning predictive and prescriptive Additionally, automate common data pulling tasks for prepping the data.
Two (2) years of experience in the travel/hospitality industry, statistics, yield management, revenue management, pricing strategy, business analysis, business planning, database management, marketing, operations research, optimization or quantitative analysis.
- Time series modeling experience: Bayesian forecasting, ARIMA, exponential smoothing,etc.
- Dataiku Data Science Studio experience preferred and ability to use advanced information systems tools
- Experience solving problems using one or more of the following machine learning techniques: Regression, Support Vector Machines, Decision trees, Random Forest, Boosting like XGBoost, PCA, K-Means, Latent Class Analysis
- Build, analyze, and compare statistical and/or machine learning models
- Tableau visualization skills preferred
- Advanced SQL querying skills
- Knowledge of quantitative / statistical modeling and evaluation
- Ability to develop and use simulation models and develop a business case for
- Ability to do predictive analytics, time series analysis and forecasting
- Ability to establish and maintain effective working relationships, both inside and outside the
Ability to communicate effectively, both orally and in writing.