About the role
AI summarisedPrincipal Data Scientist role at Apple's Worldwide Channel Strategy and Operations Data AI/ML team, focusing on designing and deploying machine learning models to enhance global sales and digital initiatives. Requires expertise in operations research, advanced ML techniques, and large-scale systems.
TechnologyFull-timeMachine Learning and AI
Key Responsibilities
- Design, develop, and deploy impactful machine learning models using large-scale datasets.
- Collaborate with multi-functional teams, including sales, engineering, analytics, and other business stakeholders, to deliver ML-driven features that enhance Apple's global sales and digital initiatives.
- Apply a wide range of modeling techniques, from traditional ML and optimization to advanced transformer-based architectures and LLM-powered components, to real-world, high-impact problems.
Requirements
- Minimum of 10 years of professional experience in machine learning, artificial intelligence, data science, or related fields, with a proven track record of delivering impactful ML solutions in industry settings.
- Advanced degree (Master's or Ph.D.) in Computer Science, Data Science, Operations Research, or a related field, or equivalent professional experience.
- Strong background in operations research, with hands-on experience applying optimization techniques (e.g., linear programming, dynamic programming, combinatorial optimization) to solve complex, real-world problems in sales or related domains.
- Deep understanding of machine learning principles, including supervised and unsupervised learning, deep learning, reinforcement learning, graph neural networks, and generative AI. Proficiency in practical implementation, hyper-parameter tuning, and performance optimization is essential.
- Exceptional ability to design and implement novel algorithms tailored to specific business needs, with a focus on scalability and efficiency.
- Proven ability to develop innovative validation frameworks to assess model performance, ensuring robustness and reliability in production environments.
- Exceptional programming skills in Python, with experience writing clean, efficient, and maintainable code. Familiarity with libraries such as TensorFlow, PyTorch, Scikit-learn, or similar is highly desirable.
- Strong ability to write complex SQL queries to extract, transform, and analyze large datasets from relational databases.
- Excellent communication and collaboration skills to work effectively with diverse teams and translate business requirements into technical solutions.
- Practical experience building and deploying ML models at scale, with a focus on real-world applications.
- Experience with transformer-based architectures or large language models (LLMs) for personalization or other applications.
- Familiarity with cloud-based ML platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks.
- Knowledge of sales and customer engagement processes, particularly in a global context.
- Ph.D. in Machine Learning, Computer Science, Mathematics, Operation Research, or a related field.