ML Data Science Manager - Marketplace Analytics, Apple Ads
ML Data Science Manager - Marketplace Analytics, Apple Ads
Posted on :
20-08-2025
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1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
20-08-2025
Job Description
The Data Insights team within Apple Ads is seeking a bright and endlessly curious data expert to lead our Core Insights team that supports the organization. This individual will be responsible for leading a team that turns the huge amounts of data generated by user searches app metadata and App Store content into business insights that improve the customer experience for the end-user as well as drive discovery and productivity for app are seeking a self-motivated leader that can execute on near-term plans and contribute to defining a longer-term vision for our team and Apple Ads. This role involves working with internet-scale data across numerous product and customer touch points; undertaking in-depth quantitative analysis on business performance; developing and running prediction and forecasting models; and building ML models including LLMs to drive core business decisions. The teams culture is focused on rapid iteration with open feedback and debate along the way plus strong collaboration with product engineering business and marketing will have experience hiring and leading large-scale sophisticated data science teams that deliver impactful insights via pattern mining anomaly detection modeling classification and creation of wide ranging analytical tooling. Successful candidates will take pride in implementing and sustaining end-to-end analytical solutions that have direct and measurable impact. The role requires both a broad knowledge of existing data mining algorithms and creativity to invent and customize when necessary.
- 10 years of data science experience with 3 years of experience leading data science or machine learning teams.
- 2 years of experience in mobile advertising and performance-based advertising platforms.
- Experience in statistical analysis machine learning models and advanced quantitative methods with a strong focus in experiment design and causal inference. Must include experience with regression classification clustering time-series analysis and LLMs.
- Exceptional programming skills in Python and SQL. Comfort with advanced analytics and data visualization tools and libraries such as Pandas R Spark and Tableau.
- Deep familiarity with commonly user Statistics and ML libraries such as ScikitLearn SparkMLLib SciPy and/or StatsModels. Familiarity Causal Inference packages such as CausalImpact DoubleML DoWhy and EconML is a big plus.
- Experience working with modern data engineering technologies and cloud-based data warehousing solutions. Familiarity with database modeling and data warehousing principles.
- Exceptional communication collaboration stakeholder management and planning skills; demonstrated success building buy-in for an innovative and bold vision.
- Must be able to guide and lead ML data scientists embedded into engineering capabilities. Seamlessly collaborate with a wide range of stakeholders including senior leadership product managers finance engineering. Able to create trust.
- Have a strategic mindset with an aptitude to condense complex concepts analysis and models into actionable data driven solutions and strategies that will propel Apples digital advertising businesses.
- Bachelors in a quantitative field such as Engineering Computer Science Statistics Applied Mathematics Econometrics Operations Research Social Sciences or equivalent professional experience.
- 15 years of data science experience with 5 years of experience leading data science or machine learning teams.
- 4 years of experience in mobile advertising and performance-based advertising platforms direct work experience in ad auctions especially keyword matching predictions ranking pricing or relevance is a big plus.
- Ph.D. or Masters in a quantitative field such as Engineering Computer Science Statistics Applied Mathematics Econometrics Operations Research Social Sciences or equivalent professional experience.
Required Experience:
Manager
Employment Type
Full Time
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