Machine Learning Data Scientist - Advertising Supply Forecasting for Apple News

The role requires experience in areas such as predictive modeling (classification and regression), optimization, industrial engineering, demand forecasting, and time-series forecasting. The ideal candidate will have working experience in deploying data science and machine learning models with large datasets in an industry setting. Deep understanding and ability to compare predictive models, evaluate their strengths and weaknesses in a particular context, and interpret and explain model results to a broad group of technical and non-technical stakeholders are also a plus.

• Experience in areas such as predictive modeling (classification and regression), optimization, industrial engineering, demand forecasting, and time-series forecasting
• Deploy data science and machine learning models with large datasets in an industry setting
• Deep understanding and ability to compare predictive models, evaluate their strengths and weaknesses in a particular context, and interpret and explain model results to a broad group of technical and non-technical stakeholders
• Experience working closely with data engineers to build efficient, scalable solutions
• Thoughtful and creative data scientist to join a team that creatively adapts state-of-the-art analytical techniques to real-world business problems

• 1+ years of professional work experience in Data Science
• Command over Python and SQL
• Comfort with cloud technologies such as AWS and Snowflake
• Experience with Big Data tools such as Hadoop, Spark and PySpark
• Experience in quantitative analysis including regression, classification, linear optimization, supply chain analytics, and time-series analyses

• 401k matching
• Health insurance
• Flight privileges
• Stock options
• Paid time off
• Retirement plan

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.