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Data Scientist - II

Employer
Warner Bros. Discovery
Location
London (Greater)
Salary
£Competitive
Closing date
22 Aug 2021

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Sector
Technology & Digital, IT
Hours
Full Time
Flexibility
Flexible working available
Contract Type
Permanent

Job Details

The Direct-to-Consumer Group is a technology company within the Discovery brand. We are building a global streaming video platform (OTT), and a suite of applications to support all of our network’s brands globally. We are building modern container-based microservices operated on AWS. Our platform covers everything from search, catalogue, video transcoding, experimentation, personalization, to global subscriptions, and much more. We build user experiences ranging from classic lean-back viewing to interactive learning applications. 

 

We build for Connected TVs, web, mobile phones, tablets, and consoles for a large footprint of Discovery-owned networks including Discovery+, Food Network, Golf TV, MotorTrend, and Eurosport.

 

We are looking for top talent, whose deep quantitative expertise and problem-solving skills are matched only by their passion for Maths and Data Design. Our team is responsible for building the Experimentation and Analytics platform for Discovery’s global digital platform. 

 

If you delight in Data Science and use the latest in Artificial Intelligence, Machine Learning, and/or Reinforcement Learning to drive data-based decisions for millions of customers across web, mobile and connected devices, then this is the role for you. 

 

As television and media habits change, our mission remains true to the principles that founded Discovery – every day we seek to ignite people’s curiosity to engage, entertain and enlighten the world around them through amazing viewing experiences.
 
The successful candidate will have a background in a quantitative or technical field, with experience of working with experimentation on large data sets. You will have experience with data-driven decision-making and Machine Learning. You are focused on results, a self-starter, and have demonstrated success in using analytics to drive the understanding, growth, and success of a product. 
 

Key Responsibilities

 

  • Collaborating with Engineers and assisting on data work. 
  • Offering enhancements to best practices and documentation. 
  • Partner with Product and Engineering teams to solve problems and identify trends and opportunities within data sets.
  • Building key data sets to empower operational and exploratory analysis
  • Automation of experiment design
  • Building and analysing dashboards and reports
  • Exploratory Analysis and Research
  • Understanding ecosystems, user behaviors, and long-term trends
  • Identifying items that help to move key metrics and influence KPIs 
  • Building models of user behaviors for analysis to power production systems
  • Influencing product teams through presentation of work
  • Communicating state of business & experiment results to product teams
  • Spreading best practices of analytics to product teams

Key Requirements

 

  • Experience of A/B testing and experimentation design. 
  • Experience of Contextual Multi Armed Bandits, Epsilon-*, Search, Ranking, Markov Chains, Attribution, Decision and other families of algorithms to help solve problems. 
  • Experience of using Monte Carlo Simulations
  • Attribution Modeling and Design (Shapley, Markov)
  • Proficient in either Python, Java or Golang. 
  • Working knowledge of the following Python Libraries: NumPy, SciPy, Scikit Learn, Pandas, Matplotlib, Plotly, Bokeh
  • SQL, NoSQL Databases, events systems, and data lakes
  • Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with our core/business products
  • Inform, influence, support and execute our product decisions and product launches.
  • Experience working with machine learning systems, designing and evaluating experiments, monitoring key product metrics, understanding root causes of changes in metrics
  • Understanding of causality and its effect on machine learning applications.

Company

The most innovative ideas and solutions come from the widest range of thoughts and ideas –and it is our people who distinguish us. The diverse minds, experiences, cultures and unique points of view of our employees give Discovery a competitive advantage.” David Zaslav, President and CEO

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