Sales - Principal AI Scientist

Imagine what you could do here. At Apple, great ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplishApple’s Worldwide Channel Strategy and Operations (WW CSO) organization drives global sales strategies, delivering innovative solutions to enhance customer acquisition, engagement, and retention. The WW CSO Data AI/ML team plays a pivotal role in building and deploying end-to-end machine learning solutions that power key business outcomes across Apple’s global sales ecosystem.By utilizing innovative AI and ML technologies, we enable personalized customer experiences, optimize sales processes, and drive measurable impact at scale.As part of the WW CSO Data AI/ML team, you’ll have the opportunity to shape the future of global sales through innovative AI and ML solutions, collaborating with some of the brightest minds in the industry. Join us to make a meaningful impact and help create experiences that delight customers around the globe. Description We are seeking a highly skilled Principal Data Scientist to join our WW CSO Data AI/ML team. This is a hands-on role where you will design, develop, and deploy impactful machine learning models using large-scale datasets. You will 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.The role requires expertise in a wide range of modeling techniques, from traditional ML and optimization to advanced transformer-based architectures and LLM-powered components, applied to real-world, high-impact problems. Responsibilities Model Development: Design and implement machine learning models, including traditional ML, optimization, deep learning, reinforcement learning, graph neural networks, and generative AI, to address business challenges in customer acquisition, engagement, and retention. Algorithm Innovation: Develop novel algorithms and optimization techniques to solve complex problems, ensuring scalability and performance in production environments. Model Validation: Invent and implement robust validation strategies to ensure model accuracy, reliability, and generalizability, leveraging both quantitative metrics and qualitative insights. Data Processing: Work with large-scale datasets, utilizing advanced data processing techniques to extract meaningful insights and prepare data for modeling. Productionization: Deploy and maintain machine learning models in production, ensuring high performance, scalability, and reliability. Multi-Functional Collaboration: Partner with sales, engineering, analytics, and other teams to align ML solutions with business objectives and integrate them into user-facing systems. Continuous Improvement: Stay abreast of the latest advancements in AI/ML and propose innovative approaches to enhance existing solutions. Minimum Qualifications Professional Experience: 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. Educational Background: Advanced degree (Master’s or Ph.D.) in Computer Science, Data Science, Operations Research, or a related field, or equivalent professional experience. Operations Research Expertise: 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. Advanced AI/ML Knowledge: 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. Algorithm Development: Exceptional ability to design and implement novel algorithms tailored to specific business needs, with a focus on scalability and efficiency. Validation Expertise: Proven ability to develop innovative validation frameworks to assess model performance, ensuring robustness and reliability in production environments. Python Proficiency: 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. SQL Competence: Strong ability to write complex SQL queries to extract, transform, and analyze large datasets from relational databases. Multi-functional Collaboration: Excellent communication and collaboration skills to work effectively with diverse teams and translate business requirements into technical solutions. Experience with Large-Scale Systems: Practical experience building and deploying ML models at scale, with a focus on real-world applications. Preferred Qualifications 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. #J-18808-Ljbffr