Digital Turbine is hiring a
Senior Data Scientist

Summary

The job is for a Data Scientist at Digital Turbine, a global operator of app growth and monetization platforms. The role involves building and deploying Machine Learning models to serve various use-cases such as predicting mobile users' favorite games, optimizing bidding prices in real-time auctions, and detecting fraud. The candidate should have 3-7 years of experience in a Data Scientist role, coding skills in Python and SQL, and familiarity with the AdTech industry.

Requirements

• Experience in the AdTech industry (AdNetwork specifically) - MUST
• 3 - 7 years of experience in a Data scientist role
• Coding in Python and SQL - MUST
• Experience with ML models around tabular datasets - MUST
• Experience with cloud environments
• Knowledge of basic and advanced concepts of Machine Learning

Responsibilities

• Building Machine Learning models and deploying them to production on a giant scale (serving 2bn devices globally and handling 200bn requests every day)
• Using ML models for various use-cases such as predicting mobile users' favorite games, predicting the value of in-app transactions, optimizing bidding prices, optimizing infrastructure utilization, detecting and eliminating fraud, and detecting image content in ads

Preferred Qualifications

• 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

Benefits

• Working for a company 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
• Being listed on Deloitte Technology Fast 500 for six consecutive years since 2015 and winner of Austin Chamber of Commerce’s Company Culture in 2020
• 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