Marketing Data Scientist
60,000-90,000 Euros + Benefits + Relocation Options
MBN is currently partnering with a world-renowned Games Development company in search of several Data Scientists to join their newly established team in Barcelona.
This role will focus on building a closer relationship between Marketing Automation and Data Science, creating value from marketing campaigns, and improving digital experiences.
The successful candidate will work with a global team both based in Barcelona, Japan, and the US.
The Marketing Data Scientist will be working with marketing performance managers to improve the effectiveness of data analytics and build lifetime value, propensity, and attribution models with the goal of improving marketing return of investment.
Remote working options are available at this time also, but the successful candidate will be required to move to Barcelona when ready to further integrate with the team.
Be a key contributor in building statistical models that predict the behaviour of the company’s player base.
Translate business needs to Data Science requirements and AB- tests in order to work with dev teams to ensure correct tracking and implementation.
Assisting in developing a Marketing Data Science strategy and to perform analysis of scenarios and AB- tests, both systematically and on a one-off basis.
Check and problem solve issues to ensure the delivery of accurate and clear analysis and reports.
Relevant experience as a data scientist, ideally within a gaming company, supporting a marketing function.
Extensive experience using R and Python for analytical purposes
Experience in predictive modeling, ideally within a gaming or marketing environment
Ability to write complex SQL queries to analyze databases consisting of millions of active users, work effectively with relational database systems
The use of data visualization libraries and implementation of data visualization tools such as Shiny or Dash.
Good knowledge / understanding of machine learning algorithms such as K-means, Random Forest for example.
Understanding the appropriate statistical techniques to use in different circumstances
Good communication skills, ability to present to stakeholders and add value in this space