Overview
On Site
Full Time
Skills
Machine Learning (ML)
Predictive modelling
Statistics
Operational efficiency
Data Science
Database modeling
Data warehouse
Big data
Software design
Real-time
Data engineering
Data Visualization
Team leadership
Data
SDS
Leadership
Analytical skill
Management
IMPACT
Fraud
Privacy
Algorithms
Regression analysis
Clustering
SQL
Apache Spark
Apache Hive
Software development
Java
Python
Debugging
Presentations
Collaboration
Agile
Research
Mentorship
Recruiting
Job Details
Summary
Apple's Strategic Data Solutions (SDS) team is looking for a talented manager who is passionate about leading a team of Machine Learning Engineers that craft, implement, and operate analytical solutions that have direct and measurable impact to Apple and its customers. You will build and lead a team of SDS data scientists, who employ predictive modeling and statistical analysis techniques to build end-to-end solutions for improving security, fraud prevention, and operational efficiency. 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 detectionFamiliarity with database modeling and data warehousing principles and SQL.Familiarity with Big Data tools like Spark, Hive etc.Strong programming skills in Java, Python, or similar languageAbility to comprehend and debug complex systems integrations spanning toolchains and teamsAbility to extract meaningful business insights from data and identify the stories behind the patternsCreativity to engineer novel features and signals, and to push beyond current tools and approachesAbility to coach data scientists and a drive to invest in team's success.Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
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 Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team Mentor data scientists for their individual career development Deliver timely, constructive feedback to help team members recognize their needs and their progress Drive the collaborative and supportive SDS culture on your team, and collaborate with peers to share best practices across the larger organization
Education & Experience
Hands-on experience as a Data Scientist or Machine Learning Engineer or equivalent role in either academia or industry Leadership experience in data science (e.g. serving as a team lead, mentoring/hiring interns or other junior data scientists, or prior management experience)
Additional Requirements
Apple's Strategic Data Solutions (SDS) team is looking for a talented manager who is passionate about leading a team of Machine Learning Engineers that craft, implement, and operate analytical solutions that have direct and measurable impact to Apple and its customers. You will build and lead a team of SDS data scientists, who employ predictive modeling and statistical analysis techniques to build end-to-end solutions for improving security, fraud prevention, and operational efficiency. 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 detectionFamiliarity with database modeling and data warehousing principles and SQL.Familiarity with Big Data tools like Spark, Hive etc.Strong programming skills in Java, Python, or similar languageAbility to comprehend and debug complex systems integrations spanning toolchains and teamsAbility to extract meaningful business insights from data and identify the stories behind the patternsCreativity to engineer novel features and signals, and to push beyond current tools and approachesAbility to coach data scientists and a drive to invest in team's success.Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
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 Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team Mentor data scientists for their individual career development Deliver timely, constructive feedback to help team members recognize their needs and their progress Drive the collaborative and supportive SDS culture on your team, and collaborate with peers to share best practices across the larger organization
Education & Experience
Hands-on experience as a Data Scientist or Machine Learning Engineer or equivalent role in either academia or industry Leadership experience in data science (e.g. serving as a team lead, mentoring/hiring interns or other junior data scientists, or prior management experience)
Additional Requirements
- To learn more about opportunities at Apple, visit 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.