About this role
Lead applied science work on large-scale forecasting and optimization systems for Amazon Shipping’s transportation network. The role sets scientific direction for production-grade machine learning solutions intended to improve delivery reliability, customer experience, costs, and network performance.
Responsibilities
- Lead and develop a team of Applied Scientists through technical guidance, mentorship, and career development. Define the scientific vision and roadmap for transportation planning and execution.
- Guide model design and experimentation using techniques that may include tree-based models, LSTMs, transformers, large language models, and reinforcement learning. Work with stakeholders to make models scalable, robust, interpretable, and production-ready.
- Partner with Product, Operations, and Engineering leaders to support proactive decisions and corrective actions. Review model performance and own business metrics tied to customer experience, cost optimization, and network reliability.
- Balance near-term delivery with longer-term innovation, and contribute publications, conference submissions, and internal knowledge sharing.
Required qualifications
At least 3 years of experience building machine learning models for business applications; a PhD, or a master’s degree with at least 6 years of applied research experience; programming experience in Java, C++, Python, or a related language; and experience with neural deep learning methods and machine learning.
Preferred qualifications
Experience with modeling tools such as R, scikit-learn, Spark MLlib, MXNet, TensorFlow, NumPy, or SciPy, and with large-scale distributed systems such as Hadoop or Spark. The listed job locations are Hyderabad, Telangana, and Gurugram, Haryana, India.