Data Science Manager

Santa Clara Valley (Cupertino), California, United States
Software and Services


Role Number:200152375
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 the App Store and Apple News! The Data Insights team within Advertising Platforms is seeking a forward-thinking and endlessly curious data expert to lead our Data Analytics team comprising data analysts and data scientists that support the Search Ads team. The Data Science Manager 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 developers. We are seeking an ambitious leader that will not only execute on near-term plans but also contribute and define a longer term vision for our team and Ad Platforms. This role will involve working with Internet-scale data across numerous product and customer touch points, undertaking in-depth quantitative analysis, reporting, and building models to drive strategy. The team’s culture is passionate about rapid iteration with open feedback and debate along the way, plus collaboration with product, engineering, business, and marketing partners. Do you have experience hiring and leading advanced analytical teams? Teams that not only deliver impactful statistical reporting but also build insights via pattern mining, anomaly detection, predictive modeling, classification, and optimization. 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.

Key Qualifications

  • 7+ years of experience leading analytics, reporting, and/or data science teams that report up to the Business. 3+ years in digital advertising and performance-based platforms.
  • Experience in advanced quantitative methods and model development with a strong focus in exploratory data science. Must include experience with regression, classification, clustering, and time-series analyses. Strong understanding of statistical theory and applications.
  • Well-rounded individual with the ability to write code to query and transform both unstructured and structured data—acting as a mentor to your team in these areas—while not being afraid to dig deep yourself.
  • Experience in cohort analysis, behavioral analytics, segmentation and sampling with hands-on A/B test design and measurement.
  • You have programming skills in Python, Java/Scala, and SQL. Demonstrated comfort with advanced analytics and data visualization tools such as Pandas, R, Spark, and Tableau.
  • Experience working with modern data technologies. Familiarity with database modeling and data warehousing principles.
  • Must be able to guide and lead analysis and model development efforts across teams of data scientists and data analysts.
  • Strategic mindset with an aptitude to condense complex concepts, analysis, and models into actionable, growth marketing data products and strategies that will propel Apple’s digital advertising businesses.
  • You're able to demonstrate your keen business sense; ability to understand and anticipate the decisions partners must make supported by data. Ability to produce and communicate data insights that into significant business impact.
  • Excellent communication, collaboration, partner management, and planning skills; demonstrated success building consensus for an innovative and ambitious vision.
  • Ability to work optimally with engineering partners to meet the data needs of the business, translating business needs into analytical requirements.
  • Familiarity with digital, performance-based marketing platforms


- Apply best-in-class modeling and analytics techniques to enable rapid insights discovery for multiple business, multi-functional teams and Senior Leadership Team (SLT) - Lead analysis of business metrics, their interactions, and framework design on deep dive investigations. Monitor usage metrics, provide business-based explanations for large scale trends and patterns in customer lifecycle behavior. Develop CLTV models. - Drive creation of self-serve analytics tools and data products to enable insights discovery at lightning speed and scale. - Automate and scale existing analysis methods. Institute new approaches on modeling and analysis frameworks. - Design and evaluate experiments that help define opportunities for increased usage, improved marketplace performance and greater customer happiness. - Guide analytics on customer journey, yield by customer cohorts, propensity modeling and behavioral analytics to drive marketing and sales strategies. Propose marketing and product changes backed by well defined experiments and data analytics. - Quantify the impact of product, sales and marketing experiences on customer happiness and future behavior. - Data mining, statistical analysis and visualization of data to help understand how developers engage with Search Ads for app promotion. Define data structures, build predictive modeling processes and find stories based on signals of advertiser success or failure/churn. - Hire and develop leading talent with relevant data science skills. Motivate and ensure success for the team by defining roles and responsibilities that are clearly communicated, define and share a strategic vision for the function, established processes, and develop personal development plans. - Empower global business teams with insights to inform and fulfill strategic objectives and goals.

Education & Experience

Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, Econometrics, Operations Research, Social Sciences, Statistics, or equivalent professional experience

Additional Requirements