At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users, app publishers, and advertisers — intelligently connecting people in more ways, across more devices. We provide app publishers and advertisers with powerful ads and experiences that captivate consumers, fuel performance, and help telecoms and OEMs supercharge awareness, acquisition, and monetization. In a rapidly evolving industry, we are constantly innovating and creating better paths of discovery to connect consumers, publishers, and advertisers across the mobile ecosystem. 

What you will do as a Senior Data Scientist at DT

 • Build Machine Learning models and deploy them to production on a gargantuan scale (We serve 2bn devices globally and handle 200bn requests every day). ML models are at the heart of our technology and serve the following use-cases:

○ Predict mobile users’ favorite games based on their previous

gaming history

○  Predict the value of the user (in-app transactions) for mobile 

game developers 

○ Optimize our bidding prices in real-time auctions 

○ Optimize infrastructure utilization

○ Detect and eliminate fraud

○ Detect image content in ads

 • Outsmart other very smart mathematicians and coders who build models for our competition. Our business is based on auctions, where having the best model yields higher-than-proportional benefits. Even a 1% improvement in model accuracy can lead to millions of dollars in earnings. Read more about the Data Science role in our business in an interview with Pawel Godula, Head of Data Science at Digital Turbine.

 • Learn data science from a great team of Data Science researchers and engineers. We have a Kaggle Grandmaster, Kaggle Master, and Kaggle experts in the team, as well as a brilliant and accomplished engineering team to support us.

Minimum Requirements:

 • Coding in Python and SQL

 • Raw intellectual horsepower (aka High IQ)

 • Ability to talk to other engineers

 • Self-motivation to achieve something remarkable

 • Knowledge of basic concepts of Machine Learning

 ○ Difference between supervised and unsupervised learning

○ Train - validation - test split

○ Accuracy metrics

○ Model classes (Gradient Boosted Decision Trees- Our favourite 

LGBM and XG Boost, Neural Networks, Regression)

*These are absolutely required

It would be amazing if you had:

 • Track record on Kaggle (please share your profile)

 • Experience with ML models in production(###---SUPER AWESOME—###)

 • Experience in data science and ad tech

About Digital Turbine:

Digital Turbine (NASDAQ: APPS) powers superior mobile consumer experiences and results for the world’s leading telcos, advertisers and publishers. Our end-to-end platform uniquely simplifies the ability to supercharge awareness, acquisition and monetization — connecting our partners to more consumers, in more ways, across more devices. 

The company is headquartered in Austin, Texas, with global offices in New York, Los Angeles, San Francisco, London, Berlin, Singapore, Tel Aviv, and other cities serving top agency, app developer, and advertising markets. Listed on Deloitte Technology Fast 500 for six consecutive years since 2015 and winner of Austin Chamber of Commerce’s Company Culture in 2020.

Digital Turbine is an equal opportunity employer committed to building a diverse and inclusive team. We welcome people of different backgrounds, experiences, abilities, and perspectives. We embed diversity in our mindset, products, and teams to empower an inclusive, equitable, and culturally fluent environment. Building this culture within our teams makes us better collaborators and partners, driving better outcomes.

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