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About the Role
The Ads Experimentation team is seeking a Machine Learning Engineer and Statistician to drive innovation in a state-of-the-art ads experimentation platform. This hands-on role involves partnering with cross-functional teams to develop and support the platform, perform rigorous analyses, measure performance, make data-driven decisions, and develop scalable tools for quick and accurate decision-making.
Responsibilities
- Design and build a new generation of experimentation platform for the Ads Platform organization.
- Apply leading-edge technologies to enable safe and data-driven launch of features.
- Collaborate with stakeholders and data scientists to design experiments and statistical methods.
- Provide expert technical guidance to engineers and scientists on statistical techniques, experiment design, and data engineering.
- Contribute to a culture that emphasizes observability, understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity, and productivity.
- Conduct rigorous, end-to-end analyses using SQL, Python, and statistical methods.
- Design and analyze controlled experiments or counterfactual causal inference studies.
- Lead the design, development, and maintenance of scalable and reliable data pipelines.
- Implement robust data quality checks, monitoring systems, and data lineage tracking.
- Advocate best practices for data engineering.
- Work directly with stakeholders, including senior leaders, to identify, scope, and prioritize high-impact questions.
- Turn analysis into clear and concise takeaways that drive action.
- Mentor junior engineers and scientists on the team.
Requirements
- 5+ years of experience in software and data science or statistics with an in-depth understanding of SQL and causal inference.
- Industry experience in SDLC is preferred.
- Experience with A/B testing infrastructure and methodologies.
- Deep understanding of the assumptions of randomized control trials.
- Familiarity with causal machine learning tools and technologies.
- Well versed in observational causal techniques like regression, propensity score matching, Diff in Diff, regression discontinuity, and instrumental variables.
- Experience in measuring advertiser value from campaigns or algorithmic changes is a huge plus.
- Proficiency in SQL and Pyspark or Scala to conduct analyses and build data products.
- Skilled at operating in a cross-functional organization.
- Ability to understand ambiguous and complex problems and design and execute analytical approaches.
- Curious business attitude with a proven ability to seek projects with a sense of ownership.
- Excellent communication, social and presentation skills.
- Desire to work in a fast-paced and challenging work environment.
Skills
- SQL
- Causal inference
- Python
- Statistical methods
- A/B testing
- Causal machine learning
- Regression
- Propensity score matching
- Diff in Diff
- Regression discontinuity
- Instrumental variables
- Pyspark
- Scala
- Data pipelines
- Dashboards
- Data quality checks
- Monitoring systems
- Data lineage tracking
Location
- Apple
Work Type
- Full-time
Experience Level
- 5+ years
- 6+ years
Education Level
- Advanced Degree in Computer Science, Statistics, Applied Math or related field
About the Company
- At Apple, we work every day to create products that enrich people’s lives.
- Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work.
- Today, our technology and services power advertising in Search Ads in App Store and Apple News.
- Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.