Amazon

Data Scientist, Amazon Ads

Job description

Description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

We are seeking a highly accomplished and visionary Data Science professional to join our team, leading our data science strategy for the Media Planning Science program. In this role, you will collaborate closely with business leaders, stakeholders, and cross-functional teams to drive the success of the program through data-driven solutions. You will be responsible for shaping the data science roadmap fostering a culture of data-driven decision-making, and delivering significant business impact through advanced analytics and cutting-edge data science methodologies.

Key job responsibilities

As a Data Scientist On This Team, You Will

  • Develop and drive the data science strategy for the Media Planning Science program, aligning it with the program's objectives and overall business goals.
  • Identify high-impact opportunities within the program and lead the ideation, planning, and execution of data science initiatives to address them.
  • Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.
  • Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
  • Apply statistical and machine learning knowledge to specific business problems and data.
  • Build decision-making models and propose solution for the business problem you define.
  • Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.
  • Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.

About The Team

The Media Planning Science team builds and deploys models that provide insights and recommendations for media planning. Our mission is to assist advertisers in activating plans that align with their goals. Our insights and recommendations leverage heuristic and machine learning models to simplify the complex tasks of forecasting, outcome prediction, budget planning, optimized audience selection and measurements for media planners. We integrate our insights into user interfaces and programmatic integrations via APIs, ensuring reliable data, timely delivery, and optimal advertising outcomes for our advertisers.

Basic Qualifications

  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of data scientist experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Bachelor's degree
  • Experience applying theoretical models in an applied environment

Preferred Qualifications

  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • PhD

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.


Company - Amazon Development Centre Canada ULC

Job ID: A2798182

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