AIML - Applied ML Researcher, Econometrics & Forecasting

We are a group of researchers and engineers at the forefront of innovations to improve Apple’s business planning through market, sales and supply chain optimizations. Our goal is to drive topline impact and strategic value for Apple - using interdisciplinary innovations. As part of our team you will play a pivotal role to apply econometric, statistical and Machine Learning methods in Apple’s product lifecycle across Finance, Sales and Operations, collaborating with world-class domain experts as well as deep-learning researchers.

Your diversity of perspectives from economics and statistics enriches the scope and scale of the business success. Does this sound exciting? Come join us!

• Demonstrated expertise with proven publication or track record in at least one of the areas: statistics, econometrics, operations research, quantitative marketing, causal inference, time series analysis, stochastic modeling, optimization and decision making theory
• Proficient in Python/R and are familiar with mainstream Machine Learning or statistical frameworks
• Demonstrated expertise in optimization methodologies such as linear programming, reinforcement learning etc.
• Proficient experience in Causal Inference and Economic models in Finance, Retail or Supply Chain areas
• In-depth experience in Deep Learning and explainable ML is a plus
• Strong business intuition, adaptive demeanor, and courage to improve established business process

Your contributions will have direct monetary impact on Apple’s business by integrating econometrics and causal inference with deep learning models to create explainable and optimized business solutions. We collaborate with outstanding engineers and researches to solve fundamental business problems:
Sales Optionality, Demand Forecasting, Supply Chain optimization and Pricing Optimization.

Ph.D. experience in Statistics, Econometrics, Operation Research, Machine Learning, Mathematics or an equivalent field, or 3+ years of industrial experience in OR, Economic Modeling or Machine Learning.