|Post Name||Senior Data Scientist, Ads Creative Suite|
|Employment Type||Full Time|
|Work Hours||8 Hours|
|Salary||CAD 48 To CAD 50 Per Hour|
|Location||Toronto, Ontario, Canada M4B 1B3|
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!
The CCS team is large and spans all advertising products and programs, with a remit to ensure customer trust in advertising. Among other things, we’re innovating and developing AI-generated solutions to building effective and compelling advertising,
As well as building ML solutions across many disciplines that help us scale our self-service ad business across the globe by ensuring we identify ads that might break our policies or not be relevant to customers, and prevent them from displaying.
We also build solutions to understand the composition of ad creatives that drive performance, and value for customers helping to make ads more effective for all. We have full stack development of core systems, as well as direct customer-facing product solutions that affect all Amazon customers.
As a Senior Data Scientist on this team you will:
- Lead Data Science solutions from beginning to end.
- Deliver with independence on challenging large-scale problems with complexity and ambiguity.
- Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data.
- Build Machine Learning and statistical models to solve specific business problems.
- Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
- Analyze historical data to identify trends and support optimal decision-making.
- Apply statistical and machine learning knowledge to specific business problems and data.
- Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions are needed.
- Give anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
- Build decision-making models and propose effective solutions for the business problems you define.
- Conduct written and verbal presentations to share insights with audiences of varying levels of technical sophistication.
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon!
About the team
- Experience in as many of the following areas: causal inferencing, multi-variate testing & design, A/B testing & design, descriptive analytics, and regression analysis.
- Good understanding of supervised and unsupervised learning models.
- Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
- Broad knowledge of ML methods, statistical analysis, and problem-solving skills.
- Expert-level knowledge in statistics and sophisticated user of statistical tools.
- Experience in data applications using large-scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
- Experience processing, filtering, and presenting large data sets (hundreds of millions/billions of rows).
- Combination of deep technical skills and business sense, to interface with all levels and disciplines within our customer’s organization.
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
- Excellent verbal and written communication skills with the ability to advocate technical solutions for science, engineering, and business audiences.
- Ability to develop experimental and analytical plans for data modeling, use effective baselines, and accurately determine cause-and-effect relations.
- Experience in computational advertising is desired, but not required.