Data Scientist Jobs at Apple Inc., Austin, United States of America

About Apple Inc.

Apple Inc. is the multinational technology company headquarters in Cupertino, California. Basically, it designs, develops and sells consumer electronics, computer software, and online services. Apple Inc. is one of the leading manufacturers of electronics like smartphone, computers, etc. In addition to that, it is one of the most reputed and biggest companies in the world. iPhone is one of the most successful products of the company.

Key functions

In particular, the successful appointee Data Scientist will perform the following specifications

• Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions. Similarly, collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions.
• Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem.
• Ensure operational and business metric health by monitoring production decision points.
• Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes. Also, communicate results of analyses to business partners and executives.
• Furthermore, research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team.

Minimum qualification

• 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
• MS. in a related field with 3+ years of experience applying data science to real business problems.

Furthermore,

• 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. Similarly, an 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.
• Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways.
• In addition to that, creativity to engineer novel features and signals, and to push beyond current tools and approaches.