The Jr. Data Scientist role is a unique employment opportunity for students seeking to gain on-the-job data science & analytics experience and receive excellent mentoring while completing their education. Jr. Data Scientists are immersed in an Amazon team and work on exciting, meaningful projects that impact real Amazon customers. Paired 1:1 with a Amazon Jr. Data Science Mentor, Jr. Data Scientists receive guidance and support in all aspects of their role: skill development, career advisement, project collaboration, and more! Upon successful completion of the Jr. Data Scientist Program, the opportunity for full-time employment may be available at an Amazon corporate site.
The Jr. Data Scientist role is part of the Jr Developer Program, a unique internship program in several respects:
• We offer employment year-round, part-time (16 hrs/week) while in school and full-time (40hrs/week) during summer. Working schedules are flexible and can be re-arranged each quarter to accommodate class schedules.
• We offer excellent mentoring. Our full-time data scientists, applied scientists and business intelligence engineers are willing and able to mentor exceptional student data scientists, applied scientists and BIEs.
• Jr. Data Scientists are given responsibilities and roles that prepare them to enter the workforce after graduation with “real world” data science and analytics experience.
Jrs. who participate in the Jr. Developer Program routinely acknowledge the valuable learning experience created by the uniform excellence of their teams, mentoring offered by experienced Amazonians, and the challenge of being a principal contributor to science and software products.
Key job responsibilities
- Create pipelines for reports, analyze massive-scale data, leverage knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages like SQL, Excel, and others, to analyze and translate the data into meaningful insights; make sense of the results and be able to explain what it all means to key stakeholders like scientists, product managers, and engineers.
- Analyze large amounts of data, discover and solve real world problems and build metrics and business cases around key performance of this program.
- Use a customer backwards approach in deriving insights and identifying actions we can take to improve the customer experience and conversion for the program.
