Manager, Data Science - Pricing Models

Marriott Hotels Resorts•Bethesda, MD

About The Position

JOB SUMMARY Applies advanced computational techniques in the development of business solutions to data-intensive problems in the hospitality industry. This rewarding position provides a career as part of a team that makes a direct revenue impact on Marriott hotels, globally, by providing tools that facilitate data-driven decision making in the disciplines of pricing, revenue management, sales and reservations. Works as part of a team that supports computationally-intensive data analysis and modeling efforts, provides pricing and statistical modeling and technical expertise; provides production support for systems deployed at our hotels; performs undirected research on large volumes of data to reach business conclusions and recommendations; contributes complex programming and analysis in revenue management and sales systems; analyzes data and builds innovative models to deliver business solutions; functions as a modeling expert in all phases of the project lifecycle – inception, prototyping, design, testing, rollout and support. The Predictive Analytics team seeks a flexible candidate with a willingness to learn that brings unique perspectives to enable creative data-driven solutions to the challenges at Marriott. CANDIDATE PROFILE

Requirements

Bachelor’s degree in a rigorous quantitative, technical or scientific subject, including Operations Research, Statistics, Mathematics, Data Science, Data Engineering, Computer Science or Engineering
Experience solving complex mathematical problems; applying analytical and programming skills against data-intensive and complex modeling
Software engineering skills (e.g. distributed computing, object-oriented development, data cleansing, algorithms and data structures)
An inherent curiosity in researching and developing solutions to complex and often open-ended business problems
An interest in continually learning new techniques and technologies to solve modeling challenges
An ability to explain and present mathematical concepts and results to technical and non-technical audiences
Strong communications skills and ability to work within a team
Knowledge of relational databases

Nice To Haves

Knowledge and experience with Python (pandas / Numpy / SciPy), SQL at an advanced level with an understanding of complexity theory
Knowledge of Stochastic process, and probability theory
Knowledge of Experiment design and causal inference methods such as difference‑in‑differences, matching, regression‑based causal models, and uplift or incremental impact analysis.
Experience with Econometric modeling and related techniques including linear and nonlinear regression, panel data models, fixed and random effects models, instrumental variables
Experience with Machine Learning tools and techniques (e.g. k-nearest neighbors, random forests, ensemble methods, etc.)
Experience with Data Platforms (i.e. Snowflake)
Experience in developing analytic driven solutions to business problems
Understands complex, discrete data sets with subtle underlying biases
Experience with linear, mixed integer, non-linear or dynamic programming models and familiarity with optimization software (CPLEX, Gurobi).
Experience with writing efficient code and an understanding of code complexity
Readiness and willingness to debug existing codes to identify source of reported application issues

Responsibilities

Provides input on solution structure, tasks, timeline and estimates for revenue management deliverables
Partners with planning teams to articulate possible solutions to business problems and to develop requirements for new models
Formulates methods for measuring the effectiveness of pricing and revenue management activities.
Prepares detailed specifications for translation of complex business processes into models and prototypes
Develops and implements efficient, scalable algorithms using appropriate technologies/software/architectures
Writes software and utility software tools to create and test new models
Assists the Application Delivery teams in support of operations
Assists the Application Delivery team in the maintenance of existing models
Provides work/cost estimates for client requests
Prepares documentation for client review.
Conducts reviews, discusses findings, risks and challenges and establishes courses of action
Follows all defined iT standards and processes and provides input for improvements to the appropriate process owners as needed
Maintains a proper balance between business and operational risk
Follows the defined project management standards and processes
Validates that Service Providers develop and manage respective aspects of a project plan, including schedules, deliverables, and appropriate metrics.
Makes short term plans for the team to effectively utilize resources
Monitors Service Provider outcomes
Reviews estimates of work effort for client project provided by Service Providers for accuracy
Facilitates timely resolution of service delivery problems and minimizes the impact to clients