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Data Scientist (Machine Learning) – Video Advertising 891 views

Amazon is investing heavily in building a customer-centric, world-class advertising business across its many unique audios, video, and display surfaces. In this role, you will be on the cutting edge of developing monetization solutions for Live TV, Connected TV, and streaming Audio. These are nascent, high growth areas, where advertising monetization is an important, fully integrated part of the core strategy for each business.

This role will work closely with scientists and engineers to develop and run statistical models to understand customer behavior and how customers respond to Amazon’s marketing. You will collaborate directly with economists to produce modeling solutions, partner with software developers and data engineers to build end-to-end data pipelines and production code, and have exposure to senior leadership as they communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, automate, and scale the analysis, and develop metrics that will enable them to continually delight their customers worldwide.

As a successful data scientist, you are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities.

Responsibilities Include

  • Build models and tools using technical knowledge in machine learning, statistical modeling, probability and decision theory, and other quantitative techniques.
  • Understand the business reality behind large sets of data and develop meaningful analytic solutions.
  • Innovate by adapting to new modeling techniques and procedures.
  • Utilizing code (Python, R, etc.) for analyzing data and building statistical models to solve specific business problems
  • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters
  • Collaborate with researchers, software developers, and business leaders to define product requirements and provide analytical support
  • Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about their systems, as well as sharing insights and recommendations

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

Preferred Qualifications

  • Master’s degree or Ph.D. in computer science, statistics, information systems, economics, mathematics, or similar
  • Multiple years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
  • Strong proficiency in SQL
  • 2+ years of relevant working experience in an analytical role involving data extraction, analysis, and communication
  • Practical understanding and hands-on experience with regression modeling (linear and logistic).
  • Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams, and business audiences
  • Direct experience with both supervised learning methods (linear and logistic regression, time-series modeling, generalized linear models, decision trees, random forests, support vector machines, etc.) and unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components).
  • Direct experience analyzing A/B experiments
  • Proven ability to convey rigorous technical concepts and considerations to non-experts
  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

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 another legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

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