Do you want to lead the Machine Learning science efforts of a growing data organization that crafts the game experiences of millions of players? Niantic, the game developer and technology powerhouse that changed the world with its groundbreaking AR, geolocation-based gaming platform used to create experiences like Pokémon GO, seeks a Director of Machine Learning Science. As an experienced scientist and manager with a track record of success, you will grow an internal team positioned to have a huge impact on the future of all Niantic titles. We are looking for a natural leader who can energize scientists to create meaningful interventions that compel players to explore the world together.

Responsibilities

  • Build and manage a team of machine learning scientists, foster collaboration, encourage their career growth, and invest in skills development.
  • Drive your team to have an impact on the business. Work collaboratively with key business partners to make it happen.
  • Lead scientists to design, develop, and optimize ML-based interventions using techniques like semi-supervised segmentation and reinforcement learning.
  • Drive a culture of scientific rigor and real world pragmatism in your team's work, particularly to quantify the impact of features on relevant engagement metrics.
  • Lead by example: promote deep scientific expertise, constant learning, attention to detail, and an intimate relationship with the data while always being friendly, humble, and open to challenging any assumptions.
  • Collaborate with data engineers, product managers, and marketing to coordinate timely deployments from conception to release.

Qualifications

  • A minimum of 4 years of experience managing a team of machine learning scientists who have developed and deployed models with material impact, preferably in a gaming context.
  • Successful candidate will have a PhD in Statistics, Machine Learning, Applied Mathematics, Computer Science, Economics, or a related field (or an MS with extensive industry experience).
  • Strong command of statistics and the science underpinning machine learning techniques and able to defend choices with math as well as real-world tradeoffs.
  • Experience leading teams that have developed and deployed ML models for classification, regression, and clustering; experience with production neural networks.
  • Proven experience leading teams that use large scale data processing (e.g. BigQuery, Spark, Hive, DataFlow/Beam).
  • Comfortable with a range of tools and languages (e.g. Python, Java, Scala, Go) and passionate about learning new technologies.

Plus If...

  • Success developing recommender systems for personalized game predictions or similar.
  • Experience applying ML models in mobile games, particularly at scale.
  • Experience working with business partners in analysis and optimization of user funnels and performance marketing.

Join the Niantic team!

Niantic is the world’s leading AR technology company, sparking creative and engaging journeys in the real world. Our products inspire outdoor exploration, exercise, and meaningful social interaction.

Originally formed at Google in 2011, we became an independent company in 2015 with a strong group of investors including Nintendo, The Pokémon Company, and Alsop Louie Partners. Our current titles include pioneering global-control game Ingress, record-breaking AR game Pokémon GO, and recently released third title, Harry Potter: Wizards Unite. 

Niantic is an Equal Opportunity employer. We believe that cultivating a workplace where our people are supported and included is essential to creating great products our community will love. Our mission emphasizes seeking and hiring diverse voices, including those who are traditionally underrepresented in the technology industry, and we consider this to be one of the most important values we hold close.

We're a hard-working, fun, and exciting group who value intellectual curiosity and a passion for problem-solving! We have growing offices located in San Francisco, Sunnyvale, Bellevue, Los Angeles, London, Tokyo, Hamburg, and Zurich.

 

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