Sr. Manager, Data Science

Key Skills

Java Programming, Python Programming, SQL, Agile methodologies, Scala Programming, Machine learning techniques, Data science techniques, Data Visualization, Deep Learning, R Programming, PySpark, SAS, Data Engineering, Large scale data processing, Data pipelines, Julia

Job Description

Welcome to Peacock, the dynamic new streaming service from NBCUniversal. Here you’ll find more than a job. You’ll find a fast-paced, high-flying team for unique birds that want to be at the epicenter of technology, sports, news, tv, movies and more. Our flock works hard to connect people to what they love, each other and the world around them by creating shared experiences through culture-defining entertainment.

As a company, we embrace the power of difference. Our team is committed to creating an organization that champions diversity and inclusivity for all by curating content and a workforce that represents the world around us. We continue to challenge ourselves and the industry by being customer-centric, data-driven creatures of innovation. At Peacock, we are determined to forge the next frontier of streaming through creativity, teamwork, and talent.

Here you can fly to new heights!

Job Description

As part of the NBCU DTC Data Science team, Sr. Manager, Data Science, Fandango, will be responsible for creating analytical solutions for Fandango including, but not limited to forecasting, recommender systems, automated marketing, commerce and revenue optimization, customer journey and CRM.

In this role, the Sr. Manager, Data Science, will serve as a team expert in advanced statistical and machine learning methodologies and lead a team of data scientists to create analytical solutions for multiple business verticals.

Responsibilities include, but are not limited to:

• Lead a team of data scientists in the development of analytical models using statistical, machine learning and data mining methodologies.
• Serve as the team expert in statistical inference, advanced statistical learning, Bayesian analysis, and other areas of mathematical statistics
• Drive the collection and manipulation of new data and the refinement of existing data sources.
• A strong understanding of the differences between inferential and predictive models and experience applying methods in both areas
• Work with business stakeholders to define priorities, approaches and business requirements for data science solutions.
• Translate complex problems and solutions to all levels of the organization.
• Drive innovation of the statistical and machine learning methodologies and tools used by the team.

Qualifications

• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
• 5+ years of combined experience in advanced analytics in industry or research.
• 1+ years of experience managing a team.
• Experience in leading a team of data scientists or/and being a lead data scientist on large commercial projects.
• Expert level knowledge of statistical methods and machine learning. Ability to define the direction for a project and select appropriate methods and tools. Up to date knowledge of recent advancements
• Experience implementing scalable, distributed, and highly available systems using Cloud Platforms.
• Experience with using data visualization tools and techniques to deliver business insights and value.
• Proficient in multiple analytics and programming languages such as R, Python, SAS, Julia, Java, Scala or similar
• Experience in data processing using SQL and PySpark.

Desired Characteristics:

• Working experience with commercial recommender systems or a lead role in research recommender system project.
• Working experience with deep learning, particularly in the areas different form the computer vision.
• Experience with reinforcement learning based systems.
• Experience with multi-billion record datasets and leading projects that span the disciplines of data science and data engineering
• Experience with commercial recommender systems.
• Knowledge of enterprise-level digital analytics platforms (e.g. Adobe Analytics, Google Analytics, etc.)
• Experience with television ratings and digital measurement tools (Nielsen, Rentrak, ComScore etc.)
• Experience building streaming data pipelines.
• Experience with large-scale video assets
• Team oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools
• Pride and ownership in your work and confident representation of your team to other parts of NBCUniversal