Summary Posted: Sep 26, 2023 Weekly Hours: 40 Role Number: 200481336 Imagine what you could do here! The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it!
Apple's WW Channel Strategy & Operations (CSO) organization focuses on developing and deploying worldwide sales programs and standard methodologies to deliver an extraordinary customer experience in the channel and drive Apple Channel sales. With deep functional expertise in digital, physical, and people enablement spaces, our WW CSO team closely collaborates with many cross-functional groups at world-wide and regional levels.
We are seeking a versatile Data Scientist/Machine Learning engineer with a passion for solving complex business problems to join our decision support and data intelligence team. As a member of this team, you will use your deep understanding of forecasting, machine learning, and deep learning to take on substantial technical problems. Key Qualifications Key Qualifications 8+ years experience in building highly scalable, compliant, and secure, enterprise-grade data and analytics platforms with robust data quality, data governance, data discovery, catalog and visualization capabilities 4+ years of experience with large-scale e-commerce data and analytics platform, including building data pipelines for Digital performance KPIs, Performance Marketing, and Testing & Optimization Strong background in mathematical modeling, linear and non-linear regression, and consumer decision making theory Ability to convey rigorous mathematical concepts and considerations to non-experts. Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark Ability to implement data science pipelines and applications in a general programming language such as Python, Scala, or Java Ability to comprehend and debug complex systems integrations spanning toolchains and teams Ability to extract meaningful business insights from data and identify the stories behind the patterns Creativity to engineer novel features and signals, and to push beyond current tools and approaches Ability to share results with a non-technical audience and advancing multiple projects at once on a tight schedule Excellent presentation, written and verbal communication, engagement and interpersonal skills along with validated skills in building great design Description Description In this role, you will focus on the following key areas:
Requirements: Understand business requirements and translate into technical solutions
Data Science: Design data science/machine learning approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem
Teamwork: Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions
Maintenance: Ensure operational and business metric health by monitoring production decision points
Analysis: Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes
Communication: Communicate results of analyses to business partners and executives
Innovation: Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team Education & Experience Education & Experience Ph.D. in Computer Science, Machine Learning, Statistics, Operations Research or related field; or
Ph.D. in Math, Engineering, Economics, or hard science with data science fellowship; or
M.S. in related field with 3+ years experience applying machine learning engineer to real business problems Additional Requirements Additional Requirements
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