Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz.
Team
Voodoo Ad-Network is an autonomous product of around 30 people that carries the ambitious mission of providing ad network services. One goal is to leverage Voodoo’s first-party data to improve Voodoo’s monetisation. Moreover, the product is growing through new ventures like opening up to external inventory, reaching the external-advertisers market and social-network monetisation through BeReal’s recent acquisition. Thanks to promising results, our ambition is now to scale up the team to support growth.
The product is composed of top-tier software engineers, infrastructure engineers, data engineers, mobile engineers, and data scientists.
The Models team is a core element of the targeting performance. It leverages machine learning and a strong business understanding to directly impact the product’s financial performance. It’s composed of mostly senior Data Analysts, Analytics Engineers, Data Engineers and Data Scientists/ML Engineers who iterate together on finding and building the next performing iteration.
This position is hybrid and requires 2-3 days per week in the office based in Paris.
Our Stack Python ⧫ Pandas ⧫ Scikit learn ⧫ LightGBM ⧫ Pytorch ⧫ Spark ⧫ SQL ⧫ Airflow ⧫ DBT ⧫ Athena ⧫ Amazon Web Services ⧫ TableauRole Improve existing models or propose new approaches to our current install rate and LTV estimation modelsBuild and deploy scalable ML systems. Swiftly tackle incidents and strive to make the system robustWork closely with product managers and other engineers to ensure that incremental ML performance translates into significant business impactDiscuss state-of-the-art ML topics with other data scientists, share ideas and challenge existing systemsGain an understanding of and engage in developing a variety of essential components to build an advertising network, including A/B testing systems, budget management, creative selection, performance monitoring, campaign optimization, app profiling, and user profilingRegularly examine the performance of the ad network to detect anomalies or propose new data-driven ideas.