2 days ago
Responsibilities
- Engage with business teams to identify opportunities, understand requirements, and translate them into technical solutions.
- Design data science approaches using established techniques or custom algorithms.
- Collaborate with data engineers and platform architects to implement production real-time and batch decisioning solutions.
- Monitor production decision points and operational and business metric health.
- Investigate adversarial trends, identify behavior patterns, and respond with logic changes.
- Communicate analytical results to business partners and executives.
Requirements
- Education in a quantitative field such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience.
- Practical and theoretical knowledge of classification, regression, clustering, and anomaly detection algorithms.
- Working knowledge of relational databases, SQL, Hadoop, and Spark.
- Ability to implement data science pipelines and applications using Python, Scala, or Java.
- Ability to understand and debug complex systems integrations across toolchains and teams.
- Ability to extract business insights and explain patterns in data.
- Strong presentation skills for communicating complex analyses and concepts to business audiences.
- Creativity in engineering novel features and signals and extending existing tools and approaches.
- Preferred experience with images, training and deploying CNN models in production, and computer vision techniques.
Tech Stack
Categories
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.