Amazon Sr Applied Scientist Amazon Devices 

United States, Washington, Seattle 

802209389

Key job responsibilities
• Build and implement advanced forecasting models using deep learning techniques, with expertise in time series analysis (trends, seasonality, stationarity) and sequence modeling architectures (RNNs, LSTMs, GRUs, Transformers) to drive decisions for pricing, promotions, and supply chain optimization.
• Write efficient, scalable production code in Python, utilizing NumPy, Pandas, and deep learning frameworks (TensorFlow/Keras, PyTorch) to develop and deploy models, while collaborating with data engineers to ensure smooth integration into real-time systems.
• Continuously optimize models through sophisticated feature engineering, hyperparameter tuning, and GPU acceleration techniques, while implementing appropriate preprocessing strategies for handling missing values, outliers, and data normalization.
• Evaluate and communicate model performance using industry-standard metrics (MAE, RMSE, MAPE), create compelling visualizations using Matplotlib, and provide actionable recommendations to cross-functional teams for pricing, promotions, and supply chain strategies.

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.