Description

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 machine learning engineers for their individual career development • Deliver timely, constructive feedback to help team members recognize their needs and their progress • Review the team's production code and logic prior to deployment • Drive the collaborative and supportive SDS culture on your team, and collaborate with peers to share best practices across the larger organization

Minimum Qualifications

• Hands-on experience as a data scientist, machine learning engineer, or equivalent role in either academia or industry
• At least 2+ years of leadership experience in data science / machine learning (e.g. serving as a team lead, mentoring/hiring interns or other junior machine learning engineers / machine learning engineers, or prior management experience)
• Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection

Preferred Qualifications

• Familiarity 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 language
• 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 coach machine learning engineers and a drive to invest in team's success.
• Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .