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  • Berlin

  • 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.

    Overview:

    As the largest independent operator of app growth and monetization platforms in the world, we help mobile game developers get more players for new games, and make more money on the games they create.

    Our business is based on real-time traffic, where having the best model yields higher-than-proportional benefits. As a data scientist, uplifting a model’s accuracy by even a 1% improvement translates to millions of dollars in earnings. If you're looking to apply your data science skills in a role that makes huge impact, we would love to hear from you!

    About the Role:

     • Building Machine Learning (ML) models and deploying them to production on a giant scale (we serve 2bn devices globally and handle 200bn requests every day).

    Using ML models which are at the heart of our technology platforms to serve the following use-cases:
    - Predicting mobile users' favourite games based on their gaming and behavioural history
    - Predicting the value of the users' in-app transactions for mobile game developers
    - Optimizing our bidding prices in real-time auctions (RTB)
    - Optimizing infrastructure utilization
    - Detecting and eliminating fraud
    - Detecting image content in ads

    Collaborating with super-smart employees from different domains - Backend, Data Engineering, Frontend, Product, Business and other Data Scientists who work on building ML models for our company

    Working with the following cutting-edge technologies:
    - AWS, GCP
    - Google, BigQuery
    - Databricks and Spark
    - Python and classic ML libraries
    - PyTorch, PyTorch Lightning
    - Experiment Management platforms such as: MLFLOW, Optuna

    About You:
     
    • Demonstrated experience with AdNetwork is required
    3 + years of experience in a Data scientist role
    Coding in Python and SQL -
    Experience with ML models around tabular datasets -
    Experience with cloud environments
    Experience with A/B testing and statistical analysis
    Knowledge of basic and advanced concepts of Machine Learning
    Fluent (native level) English language proficiency
    Ability to collaborate with other engineers
    Experience with ML models in production
    Familiarity with Spark, Databricks, MLFLOW, and Big Data related technologies - a strong advantage
    BSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning or related fields


    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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