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Senior Data Scientist, Measurement Products

Job ID: 1786734 | Amazon.com Services LLC

DESCRIPTION

Job summary
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 are strategically important to our Retail and Marketplace businesses driving 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 Ad Measurement team develops and deploys solutions fueled by machine learning to support Amazon Advertisers in their strategic campaign planning. Leaning on rich data points, we provide measurements, predictions and diagnostics that separate Amazon Advertising from all other media. To do this, our team must bring a diverse set of Statistical Machine Learning skills including Computer Vision, Deep Learning Natural Language Processing models, Marketing Mix and Response Models, and Brand Sentiment and Lift analysis.

As a Senior Data Scientist on this team, you will:
· Lead full life-cycle Data Science solutions from beginning to end.
· Deliver with independence on challenging large-scale problems with ambiguity.
· Write code (Python, R, Scala, etc.) to analyze data and build 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 decision making.
· Provide requirements to develop analytic capabilities, platforms, and pipelines.
· 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 needed.
· Given 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 solution for the business problem you defined
· Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.

Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers 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 a 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 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
· 5+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 4+ 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

· Experience in as many of the following areas: causal learning, multi-variate testing, hypothesis testing, and A/B Testing
· Experience in data applications using large scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
· Broad knowledge of ML methods, statistical analysis, and problem-solving skills.
· Expert level knowledge in Statistics; sophisticated user of statistical tools.
· Experience processing, filtering, and presenting large quantities (hundreds of millions/billions of rows) of data
· 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 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 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/us.