Full-time · Global
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.
We are the largest independent operator of app growth and monetization platforms in the world. That is, we help mobile game developers get more players for new games, and make more money on games they have already created 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 can lead to millions of dollars in earning What you have achieved..
• 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 to serve the following use-cases:
• 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, Big Query
Data bricks and Spark
Python and classic ML libraries
PyTorch, PyTorch Lightning
Experiment Management platforms such as: MLFLOW, Optuna
Requirements
BSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning or related fields
• Experience in the AdTech industry (AdNetwork specifically) - an advantage
• 3 - 5 years of experience as a Data scientist
• Coding in Python and SQL - MUST
• Experience with ML models around tabular datasets - MUST
• Experience with cloud environments
• Experience with A/B testing and statistical analysis
• Knowledge of basic and advanced concepts of Machine Learning
• Fluent English
• Ability to talk with other engineers
Advantages
• Experience with ML models in production
• Familiarity with Spark, Databricks, MLFLOW, and Big Data related technologies - a strong advantage
• Examples of great business impact that you have created
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