Data Science Manager Iap Roas Pod at Chartboost

Who we are:
Chartboost is the leading in-app monetization and programmatic advertising platform. We reach a global audience of over 700 million monthly active users and process over 2.7 trillion monthly advertising auctions. The Chartboost SDK is one the most widely integrated mobile ad SDKs and through the Chartboost Exchange, Ad Network, DSP and other services, we empower mobile app developers to build businesses, while connecting advertisers to highly engaged audiences.

We’re looking for an exceptional Manager of Data Science to join a team focused on the development of IAP ROAS (Return On Advertising Spend) Machine Learning models that power our real-time bidder, one of the most exciting and important products within Chartboost. These models help predict the propensity for a user to spend money within a mobile game, one of the key KPIs our advertising partners measure for the success of their User Acquisition strategies. The system powering this product must deal with 100,000’s of requests per second and presents unique engineering challenges. 
Impact you will make: 

Build and manage a team of Data Scientists that has a focus on maximizing the IAP ROAS for our customers
Mentor team members and help guide them in their career development
Design and test predictive models at large scale that control real money
Find new and creative ways to utilize the massive piles of data we have using both supervised and unsupervised methods
Generate insightful and actionable information driving ranking and revenue performance by using rigorous scientific and statistical methods
Train and tune learning models offline, provide clear guidelines for A/B testing and production launch
Analyze millions of structured and unstructured data points and identify meaningful features/signals to improve model performance
Collaborate closely with Product, Data, and Engineering teams to build new features and infrastructure
Define, advocate, and maintain high standards for data quality
Develop best practices for data processing, experimentation, monitoring, debugging, and analyzing data pipelines

Who you are:

BS degree in Statistics, Math, Machine Learning or Computer Science
3 to 5 years of practical experience in a Data Science or Machine Learning role
2+ years of experience managing a Data Science team
Diverse exposure to many different Machine Learning and modeling techniques such as NLP or deep networks as well as traditional modeling techniques
Ability to make progress independently: you know enough SQL to pull your own data and have mastered a programming language enough to assist you in analysis
You have a sound understanding of Data Science and Machine Learning principles

The following experience would be a plus:

Ad tech and/or Mobile space


Perks:

Competitive salary with bonuses based on performance
Restricted Stock Units (RSUs) - you will have the potential of RSUs depending on the level/role
Company sponsored daily lunch, healthy snacks, and coffee in our cool office in the centre of Barcelona - near subway and train stations
Flexible schedule based on core hours and the possibility of working from home dependent on team
English/Spanish lessons and/or other investments in your professional development
Private health insurance
Gym membership 
Transportation reimbursement
23 days of paid time off per year
15 paid holidays per year
Team building events


More about us:
We are proud of the product we've built and appreciate the impact it has on other people's businesses and lives. We want to be surrounded by people who are always finding opportunities to try something new and grow. We love data and anything that helps drive intelligent decisions and always design with the user in mind.  Sounds like a fit? Join us, and be part of the team that will change the future of mobile gaming!
We are an equal opportunity employer — we celebrate diversity and are committed to creating an inclusive environment for all employees and make our hiring decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.