Intern - Economics, FBA Science

As an Intern - Economics at Fulfillment by Amazon (FBA) Science, you will collaborate with economists and data scientists to construct data sets and perform applied econometric analysis. Your role will involve working with large datasets to address complex research questions, thereby gaining hands-on experience that is vital for your academic and professional growth.

To qualify for the Intern - Economics role at Amazon's FBA Science, you must be a PhD student in Economics, ideally in your third year or beyond and not currently on the job market. A strong foundation in econometrics and machine learning is necessary, alongside basic familiarity with Python and SQL. Attention to detail and the ability to work with large datasets will also set you apart.

An ideal candidate for the Intern - Economics position at FBA Science should possess a solid understanding of econometrics, causal inference, and machine learning. Familiarity with Python and SQL is advantageous, along with a keen attention to detail and a strong eagerness to learn and tackle research problems.

As an Intern - Economics at Amazon, you will receive competitive hourly compensation, valuable mentorship from industry professionals, and hands-on experience with real-world datasets and projects. The skills you acquire will not only aid in your academic pursuits but also significantly enhance your employability post-internship.

The career trajectory for an Intern - Economics at FBA Science is quite promising, with around 85% of previous interns successfully transitioning into full-time economist roles at Amazon. This internship is a fantastic stepping stone, offering both experiential learning and networking opportunities with industry experts.

When answering this question, highlight specific projects or coursework where you applied econometric techniques. Discuss the types of data you worked with and the methods you used to analyze that data, showcasing your ability to apply theoretical knowledge to practical problems.

Choose a project that clearly demonstrates your technical skills and strategic thinking. Outline the problem, the dataset you used, the algorithms applied, and the outcomes. Be sure to explain your role and how your contributions led to the overall success of the project.

Discuss your familiarity with tools like Python, SQL, or any other data processing software. Describe your process for cleaning and analyzing large datasets, perhaps citing specific examples where you successfully executed this in a previous project or internship.

Explain the statistical methods you have studied or used, such as regression analysis or propensity score matching. Provide examples of how you've applied these methods in a practical setting, demonstrating your understanding of the nuances involved in establishing causality.

Outline a structured approach: define the question, conduct background research, gather and prepare data, analyze it using appropriate econometric techniques, and interpret the results. Emphasize the importance of collaboration with colleagues to gain diverse insights.

Articulate your passion for economics and data analysis, and how working at Amazon's FBA Science aligns with your career goals. Highlight your interest in the innovative projects at Amazon and how you believe the experience will greatly benefit your academic and professional path.

Pick a genuine challenge, such as data quality issues or analytical complexities. Describe the problem in detail, your thought process in addressing it, and the successful outcome. This showcases your problem-solving skills and resilience.

Mention specific resources you utilize to keep your knowledge up-to-date, such as online courses, academic journals, podcasts, or industry blogs. Highlight your proactive approach to continuous learning and engaging with the economics community.

Discuss specific examples from past experiences where teamwork was crucial to project success. Emphasize your ability to communicate effectively with team members and how collaboration helps achieve common goals, especially in research settings.

Share your aspirations, whether it's contributing to impactful economic research, working in a particular industry, or pursuing further academic pursuits. Articulate how the internship at Amazon will help you lay the groundwork for achieving these goals.