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Amazon Ads exists at the intersection of marketing and ecommerce and offers advertisers a rich array of innovative advertising solutions across Amazon owned properties as well as third party properties Amazon operates. We believe that advertising, when done well, can greatly enhance the value of the customer experience and generate a positive return on investment for our advertising partners.
We are currently looking for a highly skilled and motivated Analytics and Insight Professional (AIP) to help scale our growing advertising business. The AIP is a key member of the Sales and Partner Enablement team at Amazon Advertising, working with sales, product, retail and other Amazon business partners to analyze and improve advertisers’ performance on Amazon, in support of their marketing initiatives. AIPs work with Amazon's unique data and translate it into high-quality and actionable insights and recommendations to improve the effectiveness of advertiser campaigns and unlock business opportunities. Day to day, AIP activities include analyzing metrics of success for a business or category, developing data-driven insights and recommendations for C-suite client leadership, and communicating recommendations in a clear and compelling fashion. The strategic and consultative digital expertise of an AIP is critical to delivering the best return on investment for our customers.
- Key job responsibilities
- Use Amazon’s data and your understanding of our advertising customers’ business to provide guidance to C-suite marketing leaders, via business reviews and frequent in-person client presentations to regularly iterate on and articulate a brand’s strategy
- Present findings and insights in a consultative way to the client and collaborate with the relevant internal teams in order to provide a complete solution
- Be able to deal with ambiguity in order decipher complex problems, select an ideal solution from a wide array of analytic techniques and concepts and translate into actionable requirements for your team
- Have the ability to collaborate, work cross-functionally and communicate effectively across multiple business functions and geographies
- Proactively provide appropriate levels of support and guidance to other locales outside of your core market
- Deliver regular and bespoke analyses and insights for some of the world’s largest advertisers to drive growth across advertiser KPIs and help them grow their businesses
- Demonstrate deep analytical ability, and develop great expertise in Amazon’s proprietary metrics, working to constantly evolve how we analyze and communicate data driven insights to our advertisers
- Educate other teams on Amazon media offerings and keep them engaged by delivering learning sessions, writing training documentation and whitepapers for internal and external use
- Be a proponent of data driven decision making and encourage clients to act on the recommendations
- Be someone who enjoys, and shows an appetite for, learning new skills and adopting new analytic methodologies and tools
Basic Qualifications
- Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or other related field
- Ability to translate technical aspects of analysis and metrics into actionable insights for the advertiser and both technical and non-technical stakeholders
- In depth understanding of advanced statistical techniques and methodologies as well as simple linear regression analysis, multivariate regression analysis and model building
- Advanced SQL proficiency for writing complex multi-table queries and fluency in Python (or R) for statistical modeling
- Fluency in both French and English (written & verbal)
Preferred Qualifications
- Consulting experience with a major consulting firm or advertising experience with a top advertiser (agency or client side)
- Experience with advertising publishers and marketing/creative agencies
- MBA, Master’s or Doctoral degree in Economics, Marketing, Statistics, Advertising, or Business/Digital media planning experience
- Experience in ad measurement, predictive analytics, experimental design, A/B testing
- Experience and familiarity with AWS stack
Amazon est un employeur engagé pour l'égalité des chances. Nous sommes convaincus qu'une main d'oeuvre diversifée est essentielle à notre réussite. Nous prenons nos décisions de recrutement en fonction de votre expérience et de vos compétences. Nous apprécions votre envie de découvrir, d'inventer, de simplifier et de construire. La protection de votre vie privée et la sécurité de vos données constituent depuis longtemps une priorité absolue pour Amazon. Veuillez consulter notre Politique de Confidentialité pour en savoir plus sur la façon dont nous collectons, utilisons et traitons les données personnelles de nos candidats.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
M3
M4
M5
M6
Intern
L2 · Revenue Operations L2
0 reports
$163,421
total / year
Base
$65,368
Stock
$81,711
Bonus
$16,342
$114,395
$212,447
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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