We are looking for an entry-level Quantitative Mobile Analyst to join our team and help us use data, insights, and performance-driven tactics to grow our consumer app business.

As a Quantitative Mobile Analyst, here are some examples of what you may work on:

  • Perform deep analysis of product and user quality (analysis, revenue distribution, LTV modeling, etc.) and source quality and efficiency (pricing, referral source evaluation, click-through analysis, performance management, etc.).
  • Use statistical and data visualization techniques to analyze patterns related to economics, user behaviors, and other key performance metrics.
  • Run data-driven experiments and campaigns across multiple sources of user acquisition (Facebook, Google, etc.).
  • Develop and implement data collection and analysis systems and processes.
  • Work with development team on new tools for data management and visualization.
  • Identify patterns and trends over large and complex datasets.
  • Work in cross-functional teams to meet specific goals.

You:

  • Little to no experience in mobile user acquisition or free-to-play gaming, but have a strong passion for data!
  • Healthy appreciation for mobile games.
  • 0 to 2 years data analysis experience.
  • Very strong math skills, especially statistics.
  • Excellent with MS Excel, including VBA, data analysis tools, pivot tables, and charting.
  • Strong knowledge and experience with SQL, time series, and other types of databases.
  • Strong analytical skills with an ability to collect, organize, and disseminate findings with detail and accuracy.
  • Good communication, organization, and problem solving skills.
  • Detail oriented with outstanding aptitude for self-growth.
  • Some level of experience in an office setting (internship with investment bank, consulting firm, tech company, etc.)
  • BS degree in quantitative field (math, statistics, finance, economics, computer science, physics, or related field).

Nice to have:

  • Knowledge in the areas of probability, linear algebra, and calculus.
  • Experience with statistical packages such as R or SAS.

 

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