Spanish bilingual and Hispanic jobs since 1997. Diversity job fairs since 2006. employers     login   |   register - post a job
Hispanic Diversity Recruitment - best jobs for hispanic, latino & bilingual (spanish & portuguese) jobseekers
HOME
    Log me in!   |   Site Map   |   Help   
 Director : Wallet, Payments & Commerce Data Science & BI Team - Cupertino, California, United States

   
Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Computers - Software Engineer
 
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
 
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200221413 / Latpro-3771872 
Date posted: Feb-05-2021
State, Zip: California, 95014

Description

Director : Wallet, Payments & Commerce Data Science & BI Team

Santa Clara Valley (Cupertino) , California , United States

Software and Services

Summary

Posted: Feb 4, 2021

Role Number: 200221413

At Apple, we don't just build products and services - we build things that redefine entire industries and change people's lives in important ways. It's the people that we hire that makes it all possible. The Wallet, Payments & Commerce Data Science and BI team drives insights and action for our payments businesses at Apple, supporting services used by hundreds of millions of people globally every month. Our work spans payments products such as Apple Pay, Apple Card and Apple Cash, and includes optimizing payment usage across our other Apple services such as App Store, Music, TV+ and iCloud. Apple is seeking an experienced, caring, collaborative and customer-focused Director to be the next phenomenal leader at Apple supporting the WPC Data Science and BI organization within Payments Services. This leader will continue to build a complementary team of data scientists, data engineers and BI professionals to partner with the WPC leadership, product and engineering teams. Their goals are to enable amazing customer experiences across Payment Services at Apple, teaming with the teams that build and operate these services. They and their team are responsible for delivering strategic insights that help improve the customer experience and accelerate growth for Apple Pay, Apple Card, Transit and Access, and payments and commerce for other Apple services. They should be passionate about using data to bring the vision of Apple's Payments to life, enabling a rich understanding of customer behavior and our business, and improving decision making while championing user privacy. They are enthusiastic about building data science practices and data-powered products that can help solve complicated business problems and deliver against our strategies. They are self-directed with a wide range of technical skills, and are highly proficient in turning data discoveries into analytical insights that drive business and customer outcomes. They have a deep understanding of payments, e-commerce, and credit business across the globe, with the ability to be an authority with vision at Apple .

Key Qualifications

  • A top-tier analytics professional with 10+ years of experience in forming and developing diverse teams, coordinating analytical processes and workflows, and mentoring other managers and team members from a variety of analytics & BI fields.
  • A passion for applied empirical analytics and answering hard questions with data, and the demonstrated ability to conceptualize, detail, promote and implement analytical plans that lead to business insights across the customer journey.
  • Experience crafting end-to-end measurement programs for customer acquisition and retention efforts, including marketing efficiency & optimization.
  • More than just a data science & BI lead, a demonstrated keen understanding of the Payments and Credit businesses and strategic thought leadership for Payments Services at Apple.
  • A proven track record to navigate through ambiguous and dynamic environments working with global teams on highly complex cross-functional projects. Strong capabilities to work with executive level partners as well as peers and individual contributors across a wide breadth of projects and programs.
  • Proven understanding of all aspects of a data platform, including data ingestion, data storage, data integration/ETL, SQL/NoSQL databases, and data science toolkits.
  • Excellent presentation/story tellings skills, and a love for distilling complex quantitative analysis and concepts into concise business-focused takeaways across audiences, including senior leaders/c-suite.

Description

They will lead a hardworking and growing team of Data Scientists, Machine Learning specialists, Data Engineers, and EPM's responsible for partnering with leadership to empower decision-making and improve the customer experience. They will collect, store, and analyze client and server data from customers across the world, while always keeping our dedication to customer privacy at the forefront. This data is used to generate insights that inform and drive product and marketing strategies across all of the Wallet Payments & Commerce organization. In addition to data science and ML driven optimization work, the team also develops batch and streaming analytics solutions using Kafka, Hadoop, Yarn, Spark, and other state of the art technologies in a large scale infrastructure. The team crafts and delivers self serve reporting and BI solutions for our customers using customized front ends and Tableau.

Education & Experience

Advanced degree in Applied Econometrics, Statistics, Data Mining, Machine Learning, Social Science (quantitative) Analytics, Mathematics, Operations Research, Industrial Engineering, or related field is strongly desired. Alternatively, a comparable industry career with significant experience in data analytics, ML, and data engineering.



Requirements

See job description

 

Apple requires you to fill in their on-line form which will open in a different window.

Enter your email address and click 'Apply':
       Apply
  Prefer not to enter your email?