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- Tasks: Drive data-driven decisions using econometrics and machine learning for digital ads.
- Company: Leading digital services company in Greater London with a focus on innovation.
- Benefits: Competitive salary, collaborative environment, and opportunities to influence business strategies.
- Why this job: Make a real impact on large-scale investments and work with a diverse team.
- Qualifications: PhD in Economics and proficiency in statistical tools like Python and R.
- Other info: Dynamic role with excellent career growth potential.
The predicted salary is between 40000 - 60000 £ per year.
A leading digital services company in Greater London seeks an Economist to drive data‑driven decisions using econometrics and machine learning. The role involves estimating large‑scale investments' impacts and developing econometric frameworks.
Candidates should have a PhD in Economics and strong proficiency in statistical tools like Python and R. The position offers collaboration with a diverse team of economists and data scientists to influence business strategies effectively.
Economist: Causal ML & Econometrics for Digital Ads employer: Amazon.com, Inc
Contact Detail:
Amazon.com, Inc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Economist: Causal ML & Econometrics for Digital Ads
✨Tip Number 1
Network like a pro! Reach out to fellow economists and data scientists on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your econometric models and machine learning projects. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python and R, and how you've applied them in real-world scenarios.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Economist: Causal ML & Econometrics for Digital Ads
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Economist. Highlight your PhD in Economics and any experience with econometrics and machine learning. We want to see how your skills align with the job description!
Showcase Your Skills: Don’t forget to showcase your proficiency in statistical tools like Python and R. Include specific examples of projects or analyses where you’ve used these tools to drive data-driven decisions.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your background makes you a perfect fit. We love seeing enthusiasm and a clear understanding of the position.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Amazon.com, Inc
✨Know Your Econometrics
Brush up on your econometric theories and applications, especially those relevant to digital advertising. Be ready to discuss how you've used these concepts in past projects or research, as this will show your depth of knowledge and practical experience.
✨Showcase Your Technical Skills
Since proficiency in Python and R is crucial for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common econometric analyses and be ready to explain your thought process clearly.
✨Understand the Business Context
Familiarise yourself with the digital advertising landscape and how econometrics can drive business decisions. Being able to connect your technical skills to real-world applications will impress the interviewers and show that you can contribute to their strategies.
✨Prepare for Team Collaboration Questions
This role involves working with a diverse team, so expect questions about teamwork and collaboration. Think of examples from your past experiences where you successfully worked with others, particularly in interdisciplinary settings, to highlight your ability to influence and drive results.
