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Applied Scientist, Game Ads

Job ID: 2190041 | Amazon.com Services LLC

DESCRIPTION

Job summary
This role may be located in Seattle, San Francisco or Seattle.

The Games Growth Adverting team is seeking an exceptional Applied Scientist to lead the foundation of a disruptive advertising system set to revolutionize customer acquisition for Game Developers.

This is a great opportunity to innovate on the entire breadth of the AdTech funnel, working in close collaboration with multiple science teams across Amazon Ads. You will lead the building of a platform that delivers world-class optimization for price, relevance, and reach; enabling marketers to drive user acquisition for console, mobile, and PC games. The ideal candidate will have a background in NLP, IR, Personalization or AdTech in production.



Key job responsibilities

  • Lead the design and development of large scale, performant machine learning systems in production for various AdTech use cases
  • Influence the product roadmap using data backed experiments
  • Use prior background in NLP/IR/large scale deep learning systems to explore the frontiers of supervised/semi-supervised learning enabling generalization across multiple use cases
  • Establish scalable, efficient, and automated processes for large scale model development, validation, and implementation
  • Mentor junior scientists on the team
  • Have fun working on ground breaking technology with people just as passionate about their work as you!

A day in the life
When you join The Games Growth Advertising Team, your creative partners will be some of the best from the games industry. They have built and published hundreds of the most successful video games in history. Your game studio partners are excited to build the next hit games, but they need your help. We are an Amazon team that helps game developers reach more customers who will love their games. It’s always Day-1 at Amazon, but it’s particularly Day-1 in our game growth business, and we’re excited to see what you can do.

Inclusive Culture, Work/Life Balance, & Career Growth
We embrace our differences and are committed to furthering our culture of inclusion. We offer ten employee-led affinity groups with 190 global chapters, innovative benefits, and annual and ongoing learning experiences (including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences). Our team also puts a high value on work-life balance and offers flexible working hours. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. Additionally, our team is dedicated to supporting you with mentorship and pathways for ongoing development. We have a broad mix of experience levels and tenures, and are building an environment that celebrates knowledge sharing and promotes career choice.

About the team
Game Growth Advertising applies the principles of Amazonian culture to the world of gaming user acquisition. We believe in a future where everyone is a gamer and everyone can create, compete, collaborate and connect through games, and we are looking for the right people to help us build that future. We want to be the user acquisition tool of choice for game developers across hardware platforms and gaming genres at scale. Using large scale data and state-of-the-art machine learning techniques, we are excited about shaping the future of programmatic advertising.

BASIC QUALIFICATIONS

• MS in Computer Science, strong knowledge of machine learning, and 5+ years of relevant experience in industry and/or academia OR PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
• 2 +/- years of experience using a broad set of supervised and unsupervised ML approaches and techniques ranging from Regression to Deep Neural Networks.
• Proven track record of successfully applying ML-based solutions to complex problems in business, science, or engineering.
• Ability to develop practical solutions to complex problems
• Strong communication and collaboration skills
• Proficiency in C/C++, python, and/or java

PREFERRED QUALIFICATIONS

• PhD in Computer Science or Machine Learning, AI, Statistics, Electrical Engineering or equivalent;
• More than 4 years of industrial/academic experience in building classification models
• Ability to handle multiple competing priorities in a fast-paced environment
• Significant peer reviewed scientific contributions in premier journals and conferences
• Strong personal interest in learning, researching, and creating new technologies with high customer impact
• Experience with defining research and development practices in an applied environment;
• Proven track record in technically leading and mentoring scientists;
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
• Strong fundamentals in problem solving, algorithm design and complexity analysis



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.