Job Information
Amazon Applied Scientist - Learning and Development Team, Learning Product in Nashville, Tennessee
Description
As an Applied Scientist on our Learning and Development team, you will play a critical role in driving the design, development, and delivery of learning programs and initiatives aimed at enhancing leadership and associate development within the organization. You will leverage your expertise in learning science, data analysis, and statistical model design to create impactful learning journey roadmap that align with organizational goals and priorities.
Key job 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.
Basic Qualifications
3+ years of solving business problems through machine learning, data mining and statistical algorithms experience
Master's degree in operations research, applied mathematics, theoretical computer science, or equivalent
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience programming in Java, C++, Python or related language
Experience in building machine learning models for business application
Preferred Qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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 $222,200/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.
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