Senior AI Data Scientist & Machine Learning Developer, WW CSO

Full time

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Employment Information

Job levelSenior level

IndustryComputers and Electronics Manufacturing

Experience10+ years

LocationAustin, TX, United States

Summary

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 best practices 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 an experienced AI Data Scientist & Machine Learning Developer to drive the development of our AI-driven Analytics & Decision Support Platform. In this role, you will leverage your deep expertise in developing different ML algorithms to solve real-world business challenges and accelerate operations. This includes designing and executing the best algorithmic solutions to automate and optimize operational decisions across digital, store, and people programs for all global route-to-markets. You will partner cross-functionally and multi-directionally with a variety of stakeholders to lead AI modeling initiatives, from ideation to development to post-launch improvements. As new technologies emerge, your business acumen and influence will revolutionize how our channel teams use AI and data to make decisions.

Key Qualifications

10+ 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
Outstanding communication and presentation skills, including the ability to convey technical and mathematical concepts and considerations to non-experts.
Practical experience with 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

Description

In this role, you will:

Engage with business partners to find opportunities, understand requirements, and translate those requirements into technical solutions
Design data science/machine learning approach, applying tried-and-true techniques or developing custom algorithms as needed by the business use case
Collaborate with data engineers, platform architects, software developers, data scientists/economists, and product managers to implement robust production real-time and batch decisioning solutions
Ensure operational and business metric health by monitoring production decision points
Investigate adversarial trends, identify behavior patterns, and adjust algorithms with agile logic
Communicate results of analyses to business partners and executives
Research new technologies and methods across AI models, data science, data engineering, and data visualization to improve the technical capabilities of the teams

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 5+ years of experience applying machine learning engineering to real-world business

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