Principal Data Scientist

Data Science

Full-time
Job Location: Venice, CA

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Description

System1 is hiring a Principal Data Scientist! This is a senior role with a high amount of visibility.  We are looking for experienced candidates that will bring analytical skills and statistical methods to measure the quality of our products, and to understand the behavior of end-users, advertisers, and publishers. You will be an individual contributor and build optimizations that operate in real-time on a significant amount of daily revenue.  You should be comfortable working in a highly cross-coordinated team environment where you will collaborate daily with engineering, account management and product teams. System1 is an organization centered around data and data products. We firmly believe data should inform and guide every quantitative decision process. We hire people who can utilize their broad set of technical skills to address technical challenges, as well as mentor junior team members on industry specific challenges and best practices. At System1, our Data Science team is responsible for work across the following: engineering, business, product, ETL, serving, analytics and operations.

Qualifications

  • Master’s degree in a quantitative discipline, ideally stats, is required. PhD preferred.
  • 5 years of relevant experience working hands on in industry.
  • Expertise with production data science solutions using Python and R.
  • Extensive work experience with various database technologies such as Redshift, Spark, DynamoDB, and Redis.
  • Adtech experience is preferred but not required.

Responsibilities

  • Make modeling decisions for key revenue generating projects.
  • Be a key part of developing core optimization architecture.  
  • Work directly with business stakeholders to drive optimization products forward.
  • Leadership role on an eight person team.
  • Engage in iterative analysis to provide customer level insights at scale to our company as a whole.
  • Mentor junior team members on data science best practices.
  • Work with large scale data sets.
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