Senior Machine Learning Engineer - Product Analytics
Job Summary
Job Description
Apple Ads is seeking an ML Data Scientist to join the Product and Customer Analytics Team. This role focuses on developing next-generation analytical solutions in collaboration with Sales, Marketing, Finance, Product, and Engineering. You will leverage vast amounts of data from user searches, app content, and App Store context to generate business insights that enhance customer experience and drive app discovery. Responsibilities include supporting product and executive teams with analytics, collaborating with product teams to define opportunities and KPIs, becoming a data and business expert, quantifying the impact of initiatives, managing analytics projects end-to-end, and designing experiments. You will also monitor usage metrics, explain trends, and develop reusable models with the Data Technology team.
Must have:
- 5+ years in a Data Science role
- Python and SQL programming skills
- Experience with AWS, Snowflake, Spark, Tableau
- Communicate analysis results effectively
- Work with engineering partners
- Advanced quantitative analysis experience
- Comfortable with modern data technologies
- Experience with large dataset experiments
Good to have:
- 8+ years in a Data Science role
- Experience in digital advertising or product analytics
- Hands-on experience with clickstream data
- Experience with A/B experimentation
13 skills required
Job Details
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 sponsorships 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! We're seeking an ML Data Scientist to join the Product and Customer Analytics Team. We're focused on developing the next generation of analytical solutions working with Sales, Marketing, Finance, Product, and Engineering. In this role you will work as a key member of a data-centric team to drive the exploration, analysis, development, execution, and measurement of analytical solutions that are critical to running the business. You’ll be responsible for 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 productivity for app developers.
A successful candidate will have deep experience in applied methods (predictive modeling, classification, product feature impact measurement), experience building reporting dashboards, and using those methods and tools to drive key business insights. The role requires both a broad knowledge of existing data mining algorithms, strong business sense, and creativity to invent and customize when necessary. You’ll work closely with a broad range of data professionals as well as business leaders. You’ll be working on projects where tools and methods are used to drive real-world business value. 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. - Support Product, Marketing, Partner Development, and the Executive Team with analytics for product performance and customer insight. - Work closely with the product team to identify and size new opportunities, develop data requirements, establish appropriate KPIs, and establish proper reporting. - Become an expert on both the business and the data to drive new insights. - Quantify the impact of product, sales, and marketing initiatives on customer satisfaction, and future behavior. - Manage business analytic projects through all phases, including data quality, data modeling, algorithm/KPI development, statistical analysis, data visualization, and presentation of results and deliverables. - Design and evaluate experiments that help define opportunities for increased usage, improved marketplace performance, and greater customer satisfaction. - Monitor usage metrics, understanding business-based explanations for large scale trends, and patterns in customer lifecycle behavior. - Develop reusable models and assets working closely with Data Technology team to ensure scalability and industrialization as models move into production
- 5+ years experience in a Data Science role
- Programming skills in Python and SQL, and experience with AWS, Snowflake, Spark and Tableau.
- 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 work effectively with engineering partners to meet the data needs of the business, translating business needs into analytical requirements.
- Experience in advanced quantitative analysis including regression, classification, clustering, and time-series analyses.
- Comfortable working with modern data technologies. Familiarity with database modeling and data warehousing principles.
- Practical experience working with and conducting experiments on large datasets.
- 8+ years experience in a Data Science role
- Work experience in digital advertising industry and/or product analytics. with hands on experience working with clickstream data and/or A/B experimentation.
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. Learn more about your EEO rights as an applicant.
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