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- Tasks: Analyse large datasets to solve real-world business challenges and optimise decision-making.
- Company: Join Amazon's Economic Decision Science team, a leader in economic research.
- Benefits: Gain hands-on experience with top researchers and access to unique datasets.
- Other info: Diverse and inclusive workplace with opportunities for growth and learning.
- Why this job: Make an impact by applying your economic knowledge to real business problems.
- Qualifications: PhD student in Economics or related field with skills in R, Python, and econometrics.
The predicted salary is between 20000 - 30000 £ per year.
Are you excited about applying economic models and methods using large data sets to solve real world business problems? Then join the Economic Decision Science (EDS) team. EDS is an economic science team based in the EU Stores business. The team's goal is to optimize and automate business decision making in the EU business and beyond. An internship at Amazon is an opportunity to work with leading economic researchers on influencing needle‑moving business decisions using incomparable datasets and tools. It is an opportunity for PhD students in Economics or related fields. We are looking for detail‑oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL would be a plus.
Responsibilities
- Analyze large‑scale datasets using structural econometric techniques to solve complex business challenges.
- Apply discrete choice models and methods, including logistic regression family models (such as BLP, nested logit) and models with alternative distributional assumptions.
- Utilize advanced structural methods including dynamic models of customer or firm decisions over time, applied game theory (entry and exit of firms), auction models, and labor market models.
- Build datasets and perform data analysis at scale.
- Collaborate with economists, scientists, and business leaders to develop data‑driven insights and strategic recommendations.
- Tackle diverse challenges including pricing analysis, competition modeling, strategic behavior estimation, contract design, and marketing strategy optimization.
- Help business partners formalize and estimate business objectives to drive optimal decision‑making and customer value.
- Build and refine comprehensive datasets for in‑depth structural economic analysis.
- Present complex analytical findings to business leaders and stakeholders.
Basic Qualifications
- Enrolled in a PhD program in a relevant field.
- Knowledge of statistical software such as R, Python, and Econometrics.
Preferred Qualifications
- Experience with SQL.
- Experience working with large data sets and knowledge of econometrics.
Economics - Intern - EU Stores, Economic Decision Science employer: Amazon Science
Contact Detail:
Amazon Science Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Economics - Intern - EU Stores, Economic Decision Science
✨Tip Number 1
Network like a pro! Reach out to current or former interns and employees at Amazon. They can give you insider tips on the interview process and what the team is really looking for.
✨Tip Number 2
Brush up on your data skills! Make sure you're comfortable with R, Python, and SQL. Practise analysing datasets and be ready to discuss your findings during interviews.
✨Tip Number 3
Prepare for case studies! You might be asked to solve real-world business problems using economic models. Practise structuring your thoughts and presenting your analysis clearly.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at Amazon.
We think you need these skills to ace Economics - Intern - EU Stores, Economic Decision Science
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your knowledge of econometrics and any experience with statistical software like R, Python, or Stata. We want to see how you can apply these skills to real-world problems, so don’t hold back!
Tailor Your Application: Take the time to customise your application for this internship. Mention specific projects or experiences that relate to the responsibilities listed in the job description. This shows us you're genuinely interested and have done your homework.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where appropriate to make it easy for us to read through your qualifications and experiences. We appreciate a well-organised application!
Apply Through Our Website: Don’t forget to submit your application through our official website. It’s the best way to ensure we receive your details directly and can consider you for this exciting opportunity with the Economic Decision Science team!
How to prepare for a job interview at Amazon Science
✨Know Your Econometrics
Brush up on your econometric techniques and be ready to discuss how you've applied them in past projects. Be prepared to explain complex concepts like discrete choice models or logistic regression in simple terms, as this shows you can communicate effectively with non-experts.
✨Showcase Your Data Skills
Make sure to highlight your experience with statistical software like R, Python, or Stata. Bring examples of how you've worked with large datasets, and if possible, prepare a mini-case study to demonstrate your analytical skills during the interview.
✨Understand the Business Context
Research Amazon's EU Stores and think about how economic decision science can impact their business. Prepare to discuss specific challenges they might face and how your skills can help solve them. This shows you're not just interested in the role but also in the company's success.
✨Practice Your Presentation Skills
Since you'll need to present complex findings to stakeholders, practice explaining your analysis clearly and concisely. Use visuals if you can, and be ready to answer questions. This will demonstrate your ability to communicate effectively in a business environment.