Data Scientist II, eIS Analytics
Job summaryAmazon - eIS Analytics is looking for a Data Scientist with excellent technical skills in machine learning and forecasting to drive methodology improvements and tool inventions for cost planning, goal tracking, targeting and segmentation, while developing our long term roadmap.
eIS Analytics is part of the eCommerce Foundation organization, which serves Amazon customers by leading architectural innovation and delivering technology solutions for Amazon's consumer, digital, and other businesses.
The successful candidate will be a hands-on self-starter, comfortable with ambiguity, humble to seek feedback and learn from peers, bold to think big, has solid attention to detail and believes in challenging themselves to raise the bar continuously.
The scientist will develop production models using product and resource level data on metric forecasting and service-based usage.
They will work closely with eCommerce Infrastructure Services Engineering/PM teams to understand business needs and with the Data Engineering team to productionize solutions.
This role requires an individual with excellent quantitative modeling skills and the ability to apply statistical, machine learning, econometric, and coding skills.
The candidate should have excellent communication skills to work closely with stakeholders to translate business needs into methodology and data-driven findings into actionable insights.
The successful candidate will be a self-starter comfortable with ambiguity, with excellent attention to detail, and ability to work in a fast-paced and ever-changing environment.
Key job responsibilities Simplify and drive automation of the forecasting process by building new tools and onboarding existing ones from Amazon Retail or AWS.
Design and build scalable analytic solutions using forecasting and machine learning models to measure the financial impact of products and resources within eCF.
Design and implement forecasting and machine learning models in partnership with other scientists on the team.
Work with eCF leaders and product teams on data requirements.
Work closely with both business units and engineering teams to formulate forecasting and targeting problems and associated technical solution strategies.
Work with peer science teams in Consumer to identify technical solutions that could be used or adopted in eIS Analytics forecasting and targeting framework.
Develop a library of forecasting and machine learning algorithms to enable data-driven decision making.
Support engineering teams to build tools and applications on our unique big data platform to efficiently generate and deploy insights into decision-making systems.
Raise the bar on applications of machine learning and deep learning for forecasting and targeting.
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Estimated Salary: $20 to $28 per hour based on qualifications.
eIS Analytics is part of the eCommerce Foundation organization, which serves Amazon customers by leading architectural innovation and delivering technology solutions for Amazon's consumer, digital, and other businesses.
The successful candidate will be a hands-on self-starter, comfortable with ambiguity, humble to seek feedback and learn from peers, bold to think big, has solid attention to detail and believes in challenging themselves to raise the bar continuously.
The scientist will develop production models using product and resource level data on metric forecasting and service-based usage.
They will work closely with eCommerce Infrastructure Services Engineering/PM teams to understand business needs and with the Data Engineering team to productionize solutions.
This role requires an individual with excellent quantitative modeling skills and the ability to apply statistical, machine learning, econometric, and coding skills.
The candidate should have excellent communication skills to work closely with stakeholders to translate business needs into methodology and data-driven findings into actionable insights.
The successful candidate will be a self-starter comfortable with ambiguity, with excellent attention to detail, and ability to work in a fast-paced and ever-changing environment.
Key job responsibilities Simplify and drive automation of the forecasting process by building new tools and onboarding existing ones from Amazon Retail or AWS.
Design and build scalable analytic solutions using forecasting and machine learning models to measure the financial impact of products and resources within eCF.
Design and implement forecasting and machine learning models in partnership with other scientists on the team.
Work with eCF leaders and product teams on data requirements.
Work closely with both business units and engineering teams to formulate forecasting and targeting problems and associated technical solution strategies.
Work with peer science teams in Consumer to identify technical solutions that could be used or adopted in eIS Analytics forecasting and targeting framework.
Develop a library of forecasting and machine learning algorithms to enable data-driven decision making.
Support engineering teams to build tools and applications on our unique big data platform to efficiently generate and deploy insights into decision-making systems.
Raise the bar on applications of machine learning and deep learning for forecasting and targeting.
.
Estimated Salary: $20 to $28 per hour based on qualifications.
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