Royal Caribbean is seeking a talented, experienced and inquisitive Data Scientist to design and implement cutting edge solutions across a breadth of domain areas. The ideal candidate is well grounded in a mathematical, statistical and probability background, with a broad knowledge of machine learning techniques and cognitive services.
This Data Scientist will focus on architecting, deploying and evaluating the performance of predictive solutions as part of a growing Data Science team within Royal Caribbean. This individual will work with a multidisciplinary team of driven people to deliver end to end solutions that improve guest experience and address pain points of the business across applications such as Metrics Forecasting, Custumor Behavior Prediction, Clustering, Regression, Deep Learning, Model Maintenance and Tuning, and/or statistical modelling.
Essential Duties and Responsibilities:
A successful candidate will possess a strong background or operational familiarity in statistics, mathematics, modeling (predictive, forecasting, optimization). The candidate should demonstrate a progressive maturation of prior predictive projects from ad-hoc requests to fully automated and parameterized solutions architected into broader IT systems. The candidate should also be capable of and willing to train and mentor colleagues on the proper training, development and deployment of predictive and forecasting models.
This individual will be responsible for analytical support, data mining, scripting / programming, mentor-ship and stakeholder presentation within the framework of implementing, utilizing and expanding predictive capabilities within the broader Data Science team.
Major responsibilities include:
- Apply several forms of statistical (hypothesis testing, sampling, modeling, probability, time-series) and machine learning (neural networks / deep networks, ensemble methods, natural language processing) methods to describe, predict and optimize desired analytical objectives from business stakeholders.
- Manipulates high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships and trends.
- Evaluate the progress of the data science team and company at large on the acclimation of machine learning and statistical models for predictive and forecasting tasks. Recommend steps to improve or enforce utilization of these methods.
- Empower and enhance the capabilities of the broader data science team on the proper data formatting, model selection and training, and accuracy evalution of deployed models through training, mentoring and project assistance as needed.
- Collaborate with IT, Business and Analytics stakeholders to design and implement automated and/or parameterized predictive scripts into the wider company data architecture.
- Assist with research related to customer based analytical practice and develop communications for management and strategies for building institutional knowledge. Work with product and enterprise teams via both Agile And Waterfall Methodologies.
- Foster a ‘data-driven’ culture based on pragmatism and strategic decision through rigorous factual analysis at all levels. Should be willing to engage outside the immediate team to expand data science footprint throughout organization.
- Master’s degree in Statistics, Operations Research, Mathematics, Economics, Computer Science, Engineering, Physics, Chemical Engineering or field of comparable foundations in mathematical and statistical analysis through the use of models, algorithms or programmed solutions.
- 2+ years experience with any of the following programming languages: R, Python, Java, C++, C#, Scala, SAS or similar scriptinglanguages. Similar experience and proficiency with SQL required.
- 2+ years experience with predictive and forecasting techniques and tools including time-series analysis (Autocorrelation plots, ARIMA / ARIMAX, Vector Auto Regressions, Recurrent Neural Networks), machine learning model development (grid searching, cross validation, parameter tuning & optimization), and appropriate model evaluation (ROC analysis, confusion-matrices, error rate logging)
- Experience with data mining processes (SEMMA, CRISP-DM), data preparation, consolidation, imputation, transformation, interaction, variable reduction, modeling, maintenance, and post-mortem analysis.
- Experience with statistical methods such t-test of means, Tukey-HSD tests of means on groups, ANOVA, Proportion tests, data normalization and scaling, univariate and multivariate outlier detection.
- Experience with modeling techniques such as linear models, decision trees, neural networks, k-nearest-neighbor, support vector machines, cluster analyses, and ensembling methods.
- Strong Oral and Written skills.
Preferred Qualifcations in Addition to Basic Qualifcations
- Experience with Agile Software Development
- Experience in a large corporation or consulting firm with focus in marketing strategies, modeling, CRM and management sciences/statistics highly desired
- Experience with Deep Learning tools and packages such as TensorFlow, Keras, H2O, and Theano
- Experience with frameworks and languages designed for big-data analysis, including Hadoop, Spark, Hive, and Pig
- Experience with cloud computing frameworks or API’s such as Microsoft Azure, Amazon Web Services and IBM / Watson
Knowledge and Skills:
- Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
- Has expertise in modeling, customer segmentation, analytical reporting, survey analysis, key driver analysis and dashboards.
- Demonstrates a strong capacity for learning and assimilating new techniques, tools and methods.
- Comfortable with preparing or collaborating on presentation decks as well as delivering final stakeholder presentations as primary or supporting presenter.
- Has knowledge and can quickly ramp-up and leverage cloud-based cognitive service APIs such as Microsoft Azure, AWS and/or IBM Watson.
- Is passionate about your work, but willing to support several projects at one time and can accept reprioritization as necessary.
- Comfortable delivering within an agile program.