Data Science Manager, Advertiser Experience

Data Science Manager, Advertiser Experience

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DESCRIPTION

Job summary
Amazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. The Advertising Console Product and Technology team is a group of creative individuals whose vision is to make the Amazon Advertising Console (AAC) the most loved and used tool for all advertisers to market and grow their businesses, brands, and products to a global customer base.

The AAC is a collection of federated applications that combine to form the face and brand of Amazon Advertising. ACPT owns the delivery of the software, processes, and tools that allow teams across Amazon to build, support and enhance applications and features that deliver a cohesive advertising experience to all advertisers worldwide. By using our development kit and reusable components, developers can rapidly build features that integrate seamlessly within the suite of advertiser products. We use survey research, data science, machine learning, experimentation, and predictive modeling to understand advertiser dynamics, drive platform optimization, support evidence-based decision making, and help to develop predictive, intelligent features.

As the Data Science Manager on this team, you will:

  • Lead of team of scientists, business intelligence engineers, etc., on solving science problems with a high degree of complexity and ambiguity.
  • Develop science roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects.
  • Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
  • Hire and develop top talent, provide technical and career development guidance to scientists and engineers in the organization.
  • 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 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 effective solutions for the business problems you define.
  • Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.


Why you will love this opportunity: Amazon has invested 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

  • PhD or Master’s Degree in Statistics, Applied Mathematics, Physics, Science, Engineering, Economics, or other quantitative fields.
  • 3+ years of direct people management; managing scientists.
  • 8+ years of experience as a data scientist, economist, applied scientist, research scientist or equivalent data analytics role
  • Expertise in as many of the following: hypothesis testing, estimation, experimental design, hypothesis and A/B testing, causal inferencing, multi-variate testing & design, descriptive analytics, and regression analysis.
  • Experience with data scripting languages (e.g. SQL, Python, R) or statistical/mathematical software (e.g. R, SAS, or Matlab).
  • Familiarity with probability, probability distributions, statistics and causal inference.
  • Good understanding of apply machine learning to solve real-world problems.

PREFERRED QUALIFICATIONS

  • 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.

The pay range for this position in Colorado is $175,100; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.

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.

This job is no longer open
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