Machine Learning

Descripción larga

Location : any state of Mexico

Industry - Sector : CPRS

General description

Will collaborate with the centralized Data Science team on delivering high-value AI projects across diverse business areas. These include, but are not limited to, Revenue Management, Digital, E-Commerce & Marketing, Supply Chain, and Marine Operations.

Will develop and maintain scalable AI solutions that support measurable business impact and revenue growth by combining business domain knowledge with cutting-edge technologies in Artificial Intelligence, Machine Learning, Optimization, and Big Data.

Will independently develop, productionize, and maintain AI capabilities within the Cloud to keep Royal Caribbean Cruise Lines competitive in this space.

Responsibilities

Data Scientist Responsibilities

Interpret and analyze data problems using advanced modeling techniques.

Build robust data pipelines using big-data tools.

Integrate data across different systems and streams.

Maintain data quality and integrity.

Independently develop analytic systems, predictive models, and optimization engines within a cloud environment.

Test, monitor, and improve data-driven products using industry best practices.

Continuously experiment with new machine-learning models and techniques.

Visualize data, create reports and dashboards, and develop interactive applications.

Plan projects and timelines.

Communicate effectively with business stakeholders up to the director level.

Serve as a primary contact for assigned stakeholders.

Manage change requests and urgent issues.

Data Science Skillset

Experience with statistical methods such as t-tests, ANOVA, Proportion tests, data normalization, and outlier detection.

Proficiency with modeling techniques including linear models, decision trees, neural networks, k-nearest neighbors, support vector machines, clustering, and ensembling.

Experience with Linear and Mixed Integer Optimization.

Knowledge of NLP and Deep Learning tools like TensorFlow or Keras.

Familiarity with big-data frameworks like Hadoop, Spark, or Dask.

Experience with cloud platforms such as Azure, AWS, or Google Cloud.

Experience with Agile development methodologies.

Experience in large corporations or consulting, especially in marketing, CRM, or management sciences, is highly desirable.

Strong oral and written communication skills.

Required Experience

At least 5 years of experience with programming languages such as R, Python, Java, C++, C#, Scala, SAS, MATLAB, or similar, and SQL.

Minimum 5 years of experience in data science, AI, and machine learning disciplines, including forecasting, NLP, deep learning, and computer vision.

At least 2 years deploying models in production.

At least 3 years building data pipelines.

Experience with data mining processes and data preparation techniques.

Key Words

Data science, Python, R, machine learning

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