Data Scientist — ML for Marketing Insights & Growth

Apple; Springfield (IL); On-site; USD 130,000 - 165,000; Full time

Job summary

Apple is seeking a Data Scientist – Machine Learning Researcher for the Marketing Department to transform large datasets from consumer usage, app content, and App Store settings into actionable insights that drive product and user experience.

You will research, deploy and measure ML models for marketing initiatives, collaborating with product, sales, finance and design to build business cases and product requirements, and communicating results to stakeholders to impact the overall product system.

Qualifications

• Experience in data science role.
• Hands-on experience with click-stream data and A/B experimentation.
• Strong programming in Python and SQL; proficiency with AWS, Snowflake, Flask and Spark.
• Ability to explain findings clearly to cross-functional teams.
• Experience with advanced statistical methods: regression, clustering, time-series, and commercial modeling.
• Knowledge of data-quality, data-warehousing, and data-visualization best practices.
• Comfort working with large datasets and guiding experiments at scale.

Responsibilities

• Turn large datasets from consumer usage, app content, and App Store settings into actionable insights.
• Research, evaluate, build, deploy, and measure ML models for marketing initiatives.
• Collaborate with product, sales, finance, and design teams to create business cases and product requirements.
• Communicate results to stakeholders and impact the overall product system.
• Diagnose large-scale experiments using A/B testing and analytical techniques.

Skills

Python

SQL

A/B testing

Statistical methods

Data visualization

Tools

AWS

Snowflake

Flask

Spark

Job description

Apple is seeking a Data Scientist – Machine Learning Researcher for the Marketing Department to transform large datasets from consumer usage, app content, and App Store settings into actionable insights that drive product and user experience.

You will research, deploy and measure ML models for marketing initiatives, collaborating with product, sales, finance and design to build business cases and product requirements, and communicating results to stakeholders to impact the overall product system.