Data Scientist, Advertising Revenue Recommendations

Toronto, Ontario, CAN

Full Time
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Posted 2 weeks ago

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. 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!

To be successful with Amazon Advertising, customers need to receive high quality recommendations that inform them of the right opportunities that help grow, defend and drive their business. To generate these high quality recommendations, we must discover differentiated insights that allow advertisers to understand the performance of their business over time, and performance and growth against their peers. This requires us to create models that predict successful outcomes for customers, create workflows for implementation, and measure the downstream impact of our recommendations. Our science investment in this area helps advertising customers choose when to make changes to their advertising strategy, specifies the changes to make to drive their strategy, and predicts how their business will change as a result.

Job Responsibilities:
· Contribute to customer-facing products; provide insights and metrics to track recommendation performance & downstream impact.
· Solve real world problems by analyzing large amounts of business data, diving deep to identify business insights and opportunities, designing simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.
· Utilize code (Python, R, Scala, etc.) to analyze data and build statistical models to solve specific business problems.
· Apply statistical or machine learning knowledge to specific business problems and data.
· Build decision-making models and propose solution for the business problem you defined
· Translate business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies. In cases where questions cannot be answered with available data, work with engineers to produce the required data.
· Deliver with independence on challenging large scale problems with ambiguity.
· 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 decision making.
· Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
· Provide requirements to develop analytic capabilities, platforms, and pipelines.
· Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.
· Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
· Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.

Why you love this opportunity
Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

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! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.

Team video https://youtu.be/zD_6Lzw8raE

Basic Qualifications


· Bachelor's Degree
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 2 years working as a Data Scientist
· 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.

Preferred Qualifications

· PhD in Statistics, Economics or related quantitative field.
· Experience in measurement problems, causal inferencing, multi-variate testing & design, A/B testing & design, manipulating data & analyzing very large data sets, descriptive analytics, and regression analysis.
· Excellent quantitative modeling, good knowledge of ML methods, statistical analysis, and problem-solving skills.
· Experience processing, filtering, and presenting large quantities (millions to billions of rows) of data.
· Experience using ML libraries, such as scikit-learn, caret, mlr, mllib
· Combination of deep technical skills and business savvy enough 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 effectively advocate technical solutions to scientists, engineering, and business audiences.
· Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
· Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
· Experience in advertising is a plus.

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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us

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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/ontario


Job tags: Economics Engineering Machine Learning Matlab ML Python R Research Scala Scikit-Learn SQL
Job region(s): North America
Job stats:  15  2  0
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