Machine Learning Data Scientist - Predictive Semantics Team, Apple Ads

Machine Learning Data Scientist - Core Insights, Apple Ads

Cupertino, California, United States Software and Services

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses. Our technology powers ads and sponsor ships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: we respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands.

Because when advertising is done right, it benefits everyone.

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 demonstrated capability to 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 are also a plus.

Competitive candidates will also have experience working closely with data engineers to build efficient, scalable solutions. We are looking for a thoughtful and creative data scientist to join a team that creatively adapts state-of-the art analytical techniques to real‑world business problems with an approach focused on rapid development, evaluation, and iterative improvement. Continuous learning is part of the job, both as it relates to technical skills and within the content and format of advertising domain.

• 4+ years of recent experience in a data science role.
• Bachelor's in computer science, mathematics, or another quantitative field
• 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.
• Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product.
• Ability to partner with engineering, meet the data needs of the business, find creative analytical solutions, and develop initial prototypes to address business problems.
• Experience with end-to-end implementation of a model prototype specifically training, processing, feature engineering, evaluating model outputs, and putting models into production.

• 5+ years of experience in Business Analytics, Data Science, or a related analytical role
• Strong data analysis skills, including the ability to conduct deep dives using statistical methods and data science techniques
• Exceptional communication skills, with the ability to communicate complex analyses clearly to executive and technical audiences
• Demonstrated ability to collaborate with cross-functional partners such as Product, Sales, and Marketing to design experiments and analyses that inform business decisions
• Proficiency in SQL and data visualization, with a strong eye for design and clarity
• Strong programming skills in Python, with experience using libraries such as Pandas, Sci Py, and scikit-learn
• Comfortable querying and analyzing large datasets using tools such as SQL, Snowflake, or similar analytical data platforms
• Bachelor’s degree in a related field, or equivalent industry experience

• Experience in the digital advertising industry or a related field and/or experience with demand forecasting
• Willingness to learn, both technically and in the domain of the data.
• Familiarity with packages like numpy, pandas, scikit-learn, and prophet
• Familiarity with job orchestration frameworks like git, Airflow, CI/CD, Kubernetes, Docker, Jenkins.
• Experience and/or interest in deep learning, LLMs, and Natural…