Overview
On Site
Full Time
Skills
Machine Learning (ML)
Predictive modelling
Statistics
Operational efficiency
Data Science
Relational databases
Software design
Real-time
Computer science
Data
SDS
Analytical skill
Management
IMPACT
Fraud
Manufacturing
Privacy
Algorithms
Regression analysis
Clustering
SQL
Apache Hadoop
Software development
Python
Scala
Debugging
Presentations
Collaboration
Agile
Mathematics
Job Details
Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.Apple's Strategic Data Solutions (SDS) team is looking for a hardworking individual who is passionate about crafting, implementing, and operating analytical solutions that have direct and measurable impact to Apple and its customers.As an SDS Machine Learning Engineer, you will employ predictive modeling and statistical analysis techniques to build end-to-end solutions for improving security, fraud prevention, and operational efficiency across the company, from manufacturing to fulfillment to apps and services.Apple's dedication to customer privacy, the adversarial nature of fraud, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, we will push the limits of existing data science methods while delivering tangible business value!
Key Qualifications
Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detectionWorking knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and SparkAbility to implement data science pipelines and applications in a general programming language such as Python, Scala, or JavaAbility to comprehend and debug complex systems integrations spanning toolchains and teamsAbility to extract meaningful business insights from data and identify the stories behind the patternsExcellent presentation skills, distilling complex analysis and concepts into concise business-focused takeawaysCreativity to engineer novel features and signals, and to push beyond current tools and approaches
Description
Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem Collaborate with data engineers and platform architects 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 respond with agile logic changes Communicate results of analyses to business partners and executives
Education & Experience
PhD in Computer Science, Statistics, Applied Math or a related field and 5+ years of industry experience OR MS in related field with 7+ years hands-on industry experience
Additional Requirements
Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.Apple's Strategic Data Solutions (SDS) team is looking for a hardworking individual who is passionate about crafting, implementing, and operating analytical solutions that have direct and measurable impact to Apple and its customers.As an SDS Machine Learning Engineer, you will employ predictive modeling and statistical analysis techniques to build end-to-end solutions for improving security, fraud prevention, and operational efficiency across the company, from manufacturing to fulfillment to apps and services.Apple's dedication to customer privacy, the adversarial nature of fraud, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, we will push the limits of existing data science methods while delivering tangible business value!
Key Qualifications
Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detectionWorking knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and SparkAbility to implement data science pipelines and applications in a general programming language such as Python, Scala, or JavaAbility to comprehend and debug complex systems integrations spanning toolchains and teamsAbility to extract meaningful business insights from data and identify the stories behind the patternsExcellent presentation skills, distilling complex analysis and concepts into concise business-focused takeawaysCreativity to engineer novel features and signals, and to push beyond current tools and approaches
Description
Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem Collaborate with data engineers and platform architects 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 respond with agile logic changes Communicate results of analyses to business partners and executives
Education & Experience
PhD in Computer Science, Statistics, Applied Math or a related field and 5+ years of industry experience OR MS in related field with 7+ years hands-on industry experience
Additional Requirements
- To learn more about opportunities at Apple, visit ;/li>
- 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.