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Description

Workforce Solutions – Employee Engagement Solutions team focuses on improving employee experience at Amazon, driving productivity and retention, and resulting in a motivated workforce of over 1.5 million associates and corporate employees. These are the questions we ask — Are we facilitating the right conversations to build an engaged workforce? What trends are we seeing in our employee data and what should managers do about it? How do we solve customer problems in the most efficient way possible? If these challenges sound interesting to you, you want to be a part of building ‘first of their kind’ products, and you are passionate about putting employee experience first, consider the Workforce Solutions team. Our org helps Amazon drive improvements in employee talent outcomes (e.g., job satisfaction and retention), and strive to be Earth’s Best Employer through scalable technology.

We are looking for a customer-obsessed Data Scientist for Employee Engagement Solutions, a suite of internal employee engagement and recognition products supporting Amazonians worldwide, with a strong track record of delivering results and proven research experience. This role will own and execute strategic cross-functional employee engagement experiments, analysis and research initiatives across Operations and Corporate audiences for high CSAT (Customer Satisfaction) products. The Data Scientist must love extracting, cleaning and transforming high volume of data into actionable business information and be able to drive actionable insights.

Key job responsibilities

• Implement statistical methods to solve specific business problems utilizing code (Python, R, Scala, etc.).

• Drive design and development of user classification/predictive models through NAWS based data pipelines to enable a personalized experience for a user.

• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.

• Collaborate with product management, software developers, data engineering, and business leaders to define product requirements, provide analytical support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models.

• Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance.

• Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations.

• Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology

A day in the life

The data scientist will partner with Product, UX and Dev teams to own end-to-end business problems and metrics with a direct impact on employee experience. Success in this role will include delivering solutions with measurable business impact. The problems you will consider will be difficult to solve and often require a range of data science methodologies combined with subject matter expertise. You will need to be capable of gathering and using complex data set across domains. You will deliver artifacts on small to medium sized projects, define the methodology, and own the analysis. Your findings will affect important business decisions. Solutions are testable and reproducible. You will create documents and share findings in line with scientific best practices for both technical and nontechnical audiences.

About the team

You will be part of the Employee Engagement Solutions team within the Workforce Solutions Organization. The Employee Engagement team owns the full suite of employee facing products such as Thrive, Engage, Gather, and Conversation Hub.

Basic Qualifications

- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience

Preferred Qualifications

- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R

- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

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, 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 $97,500/year in our lowest geographic market up to $185,000/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.