Data Science Manager - Search Ads
Santa Clara Valley (Cupertino), California, United States
Software and Services
Search Ads in the App Store is an easy, efficient, and fast-growing platform for app discovery. With over 65% of all app downloads resulting directly from a search on the App Store, Search Ads delivers highly motivated, quality customers for iOS developers. For more information, see http://searchads.apple.com. Apple is seeking a bright and endlessly curious data expert to manage a team of data scientists that support the Search Ads team. The Data Science Manager will be responsible for leading the team that turns 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. You will have experience hiring and leading advanced analytics teams, as well as a focus in applied research with expertise in pattern mining, anomaly detection, predictive modeling, classification, and optimization. You 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.
- Excellent communication, collaboration, partner management, and planning skills; demonstrated success building consensus for an innovative and bold vision. Demonstrated business insight; ability to understand and anticipate the decisions partners must make supported by data.
- Ability to produce and communicate data insights that translate into significant business impact 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 afraid to dig in and go deep.
- Programming skills in Python, Java/Scala, and SQL, and comfort with advanced analytics tools such as Pandas, R, Spark, and Tableau.
- 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.
- Deep understanding of statistical theory and applications. Practical experience working with and conducting experiments on large datasets.
- Ability to work effectively with engineering partners to meet the data needs of the business, translating business needs into analytical requirements.
- 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. Familiarity with digital, performance-based marketing platforms.
Hire and develop leading talent with confirmed, relevant data science skills. Motivate and set the team up for success by ensuring that roles and responsibilities are clearly communicated, the strategic vision for the function is defined and shared, processes are established, and personal development plans are developed. 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 CLTV models. Quantify the impact of product, sales and marketing experiences on customer satisfaction and future behavior. Forecast performance and yield by customer cohorts; create propensity models to drive marketing and sales strategies. Develop bid / budget recommendations for advertisers. Propose marketing and product changes backed by well-defined experiments and data analytics. Analytics, statistical analysis and visualization of data to help understand how developers engage with Search Ads for app promotion. Define data structures, create predictive modeling processes and find stories based on signals of advertiser success or failure/churn. Empower the global Partner Development teams with insights to inform and fulfill their strategic objectives and goals for every fiscal quarter.
Education & Experience
Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, Social Sciences, Statistics, or equivalent professional experience Apple is an equal opportunity employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants.