Amazon
Applied Scientist
The Applied Scientist will develop and improve time series forecasting models for Amazon Devices. With a focus on addressing the cold-start problem for new, unlaunched devices, they will implement and refine machine learning models that can accurately forecast demand patterns across different price points and seasonal periods for new Amazon devices. This role offers an excellent opportunity to tackle complex forecasting challenges where historical data is limited or non-existent, requiring innovative solutions to capture potential demand signals, seasonal trends, and price elasticity for unreleased products. The scientist will analyze how pricing strategies and seasonal events impact consumer behavior and incorporate these insights into predictive models to better anticipate market demand. Key job responsibilities: Develop and implement forecasting models using Python, focusing on techniques that address the cold-start problem for new Amazon Devices, including transfer learning from similar products and incorporating external factors that may influence demand. Apply deep learning frameworks (TensorFlow/Keras, PyTorch) to build sequence models (RNNs, LSTMs) that can effectively utilize limited pre-launch data and proxy information to forecast seasonal trends and price-sensitive demand for new devices. Conduct sophisticated feature engineering tasks, leveraging data from product attributes, market trends, and consumer preferences to create informative features for forecasting demand of unlaunched devices. Evaluate model performance using appropriate metrics for cold-start scenarios, create visualizations to illustrate forecast uncertainty, and present findings to cross-functional teams to inform launch strategies and initial inventory decisions. Implement and continuously improve methodologies for incorporating early sales signals and rapidly adjusting forecasts as new Amazon Devices enter the market. Basic qualifications: 3+ years of building models for business application experience PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience Experience programming in Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred qualifications: Experience using Unix/Linux Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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, please visit
amazon.jobs/content/en/how-we-hire/accommodations
for more information. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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.
The Applied Scientist will develop and improve time series forecasting models for Amazon Devices. With a focus on addressing the cold-start problem for new, unlaunched devices, they will implement and refine machine learning models that can accurately forecast demand patterns across different price points and seasonal periods for new Amazon devices. This role offers an excellent opportunity to tackle complex forecasting challenges where historical data is limited or non-existent, requiring innovative solutions to capture potential demand signals, seasonal trends, and price elasticity for unreleased products. The scientist will analyze how pricing strategies and seasonal events impact consumer behavior and incorporate these insights into predictive models to better anticipate market demand. Key job responsibilities: Develop and implement forecasting models using Python, focusing on techniques that address the cold-start problem for new Amazon Devices, including transfer learning from similar products and incorporating external factors that may influence demand. Apply deep learning frameworks (TensorFlow/Keras, PyTorch) to build sequence models (RNNs, LSTMs) that can effectively utilize limited pre-launch data and proxy information to forecast seasonal trends and price-sensitive demand for new devices. Conduct sophisticated feature engineering tasks, leveraging data from product attributes, market trends, and consumer preferences to create informative features for forecasting demand of unlaunched devices. Evaluate model performance using appropriate metrics for cold-start scenarios, create visualizations to illustrate forecast uncertainty, and present findings to cross-functional teams to inform launch strategies and initial inventory decisions. Implement and continuously improve methodologies for incorporating early sales signals and rapidly adjusting forecasts as new Amazon Devices enter the market. Basic qualifications: 3+ years of building models for business application experience PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience Experience programming in Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred qualifications: Experience using Unix/Linux Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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, please visit
amazon.jobs/content/en/how-we-hire/accommodations
for more information. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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.