Sr. Data Scientist

This is a Full Time Job

The Senior Data Scientist will be responsible for collaborating with other data scientists in developing and executing the Data Science and Machine learning Roadmap for WWE. Reporting to the Head of Data Science, this person will build models that drive data insights and decision making across all LOBs by building the next generation of data products, leveraging machine learning algorithms and data science, and following reproducible, auditable, collaborative development practices. Some illustrative examples include building topic models to get insight into fan conversation (using Twitter, YouTube, et al), developing forecasting models for TV, Digital ratings, and e-commerce sales. The role will report to the VP of Data Science.

They will work closely with the business teams at WWE and the data analytics business partners to identify use cases, convert them into analytical problems and build solutions and/or products fit for purpose. They will leverage WWE's data management platform and work closely with our tech teams responsible for managing various parts of the data stack. Our environment is dynamic, fast-paced, and lots of fun.

Key Responsibilities
• Developing new models and techniques to improvise our core ML platform capabilities
• Mentor a strong team of junior data scientists and ML engineers
• Report research findings to various stakeholders and publish them internally and externally as necessary
• Collaborate with other data scientists and ML engineers to productize models in the production
• Develop models to use the wealth of available data stored in a variety of internal and external data stores to deliver meaningful insight to drive the decision-making process
• Focus on automation and utilizing technology to provide repeatable solutions; Drive optimization and efficiency initiatives to support reduced cycle time
• Identify processes and develop tools to help monitor and analyze model performance and data accuracy using established processes, tools, and methodologies
• Cross-collaborate with analytical teams and other business stakeholders to operationalize their analysis and models so that they can be seamlessly integrated into stakeholders and partner workflows
• Help build the creation and maintenance of required documentation for all owned deliverables

Qualifications

Must have:
• 4+ years of hands-on, technical experience with data analytics, data science, and/or engineering.
• Proficient in Python and at least 1 of Spark, Scala, R, SQL, C++, or MatLab.
• Expert in developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, parameter tuning, etc.).
• Experience in evaluating and making decisions around the use of new or existing tools for a project.
• Experience initiating and driving projects to completion autonomously.
• Proven ability to work well in a dynamic, fast-paced environment and demonstrated initiative in taking ownership for all assigned responsibilities, deliverables, and results.
• Create compelling interactive visualizations and presentations to enhance decision-making capabilities throughout the company.
• Curiosity and passion about, and wants to stay on top of all the cool things happening in the rapidly evolving data science world.

Nice to Have:
• Master's degree / Ph.D. in mathematics, applied statistics, information technology, or a related field or equivalent experience
• Practical experience with ML platforms such as Tensorflow/Keras, PyTorch, etc.
• Advanced knowledge in model evaluation, tuning and performance, operationalization and scalability of scientific techniques, and establishing decision strategies.
• Proficient understanding of fundamental AI and ML techniques; e.g., A*, regularization.
• Expertise in one or more specialized areas; e.g., deep learning (DL), reinforcement learning (RL), planning, information representation and retrieval, graphs, multi-agent systems (MAS), computational game theory, natural language processing (NLP).
• Experience working in the media/sports industry.

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