ML Data Scientist

At Apple, we believe in the power of technology to enrich people's lives. Everything we build is designed to empower people, including our advertising platform. We deliver ads in a way that benefits both consumers and advertisers — helping people discover content, supporting creators, and protecting and respecting everyone's privacy.

Our technology makes advertising possible on the App Store, Apple News, Stocks, and Apple TV. We help developers and marketers of all sizes drive app discovery across the App Store. Our display ads on Apple News and Stocks let advertisers promote their products alongside trusted content in a brand-safe environment, while supporting publishers and journalists. Sponsorship integrations and experiences in live sports on Apple TV help advertisers connect with captivated audiences. Everything we do is with the unwavering commitment to privacy you expect from Apple. Because when advertising is done right, it benefits everyone.

Description
Our platforms are highly performant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy. The Ad Platforms Data Insights team is seeking a Data Scientist to join in developing the next generation of analytical solutions in collaboration with Engineering, Product, Sales, Marketing, and Finance. In this role you will work as a key member of a data-centric team to drive the exploration, analysis, development, execution, and measurement solutions that are essential to running and growing the ads marketplace. Responsibilities include turning the huge amounts of data generated by user searches, app content, and App Store context into business insights that improve the customer experience for the end-user as well as drive discovery and efficiency for app developers.

This role requires both a broad knowledge of statistics and creativity to invent and customize when vital. You'll dig in and get into the details. The theory behind the techniques are just the beginning. You'll be working on projects where practical applications of these approaches get applied in real-world scenarios. Successful analytics teams involve data scientists and data engineers working hand in hand to build insightful and efficient solutions. In your role, you will be a key player in a multi-functional team that delivers insights that have direct and measurable impact. We're looking for an inquisitive, collaborative, and passionate person to join this amazing team.

Minimum Qualifications
Recent experience in a data science role.
Programming skills in Python and SQL, and familiarity with machine learning, such as scikit-learn, xgboost, PyTorch, SciPy is necessary.
Familiar with statistical analysis methods, most notably regression analysis, causal inference, statistical learning and A/B and quasi-experimentation methods.
Demonstrated experience in applying statistics and machine learning to generate clear actionable insights.
Comfortable with a variety of data stores such as Hadoop, and Snowflake, familiar with distributed analytics engines such as Spark/PySpark.
Possess exceptional communication skills to communicate analyses in a clear and effective manner to technical audience and executive leadership.
Demonstrated ability to partner with engineering, meet the data needs of the business, finding creative analytical solutions and develop initial prototypes to address messy business problems.
Proven ability to operate comfortably and optimally in a fast-paced and constantly evolving environment.
Bachelor's degree in Data Science, Applied Mathematics, Statistics, Computer Science or relevant field/experience

Preferred Qualifications
2+ years of recent experience in a data science role.
Experience in the mobile advertising industry or related field.
Familiarity with job orchestration frameworks such as Airflow.
Demonstrated ability to build visualizations, dashboards and enable broader consumption of insights and tools for investigations.
Post-Bachelor's degree in Data Science, Applied Mathematics, Statistics, Computer Science or relevant field/experience

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