Sr. Data Scientist , Product Science & Analytics

Job Description

Locations

• United States, WA, Bellevue, Bellevue, WA, United States

Salary

Salary not disclosed

Skills Required

• - 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experienceintermediate
• - 4+ years of data scientist experienceintermediate
• - Experience with statistical models e.g. multinomial logistic regressionintermediate

Required Qualifications

• - 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience (experience, 5 years)
• - 4+ years of data scientist experience (experience, 4 years)
• - Experience with statistical models e.g. multinomial logistic regression (experience)

Preferred Qualifications

• - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience (experience, 2 years)
• - Experience managing data pipelines (experience)
• Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/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. (experience)

Responsibilities

• 1) Research and Analysis:
• - Conduct research on learning and development trends, theories, and best practices related to leadership and associate development.
• - Analyze data to identify learning needs, performance gaps, and opportunities for improvement within the organization.
• - Use data-driven insights to inform the design and implementation of learning interventions.
• 2) Program Design and Development:
• - Collaborate with cross-functional teams to develop comprehensive learning programs focused on leadership development and associate growth.
• - Design learning experiences using evidence-based instructional strategies, adult learning principles, and innovative technologies.
• - Create engaging and interactive learning materials, including e-learning modules, instructor-led workshops, and multimedia resources.
• 3) Evaluation and Continuous Improvement:
• - Develop evaluation frameworks to assess the effectiveness and impact of learning programs on leadership development and associate performance.
• - Collect and analyze feedback from participants and stakeholders to identify strengths, areas for improvement, and future learning needs.
• - Iterate on learning interventions based on evaluation results and feedback to continuously improve program outcomes.
• 4) Thought Leadership and Collaboration:
• - Serve as a subject matter expert on learning science, instructional design, and leadership development within the organization.
• - Collaborate with stakeholders across the company to align learning initiatives with strategic priorities and business objectives.
• - Share knowledge and best practices with colleagues to foster a culture of continuous learning and development.

Documents

• Accommodations Information (web)
• https://www.aboutamazon.com/workplace/employee-benefits (web)

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