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Description

The Sr. Applied Scientist will be responsible for building advanced time series forecasting models for Amazon Devices using deep learning techniques and state-of-the-art sequence modeling approaches. They will develop scalable, accurate predictive models leveraging RNNs, LSTMs, and Transformer architectures to drive key decision making that supports critical business decisions (including pricing, promotions and supply chain) for all of Amazon consumer hardware product lines WW. Collaborating with cross-functional teams, they will integrate these models into operational systems to enhance data-driven decision-making and optimize business outcomes. Strong expertise in time series analysis, deep learning frameworks, and computational efficiency will be key to success in this role.

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.

Basic Qualifications

- 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

Preferred Qualifications

- 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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.