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Senior Data Scientist

Kabam
Vancouver
2 years ago
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The senior data scientist advocates for machine learning to change the way we make and operate our world-class games. You will lead a team to design and implement end-to-end machine learning systems for production.

Working alongside the most talented data scientists and analysts in the data science and analytics department; a centralized department that works with stakeholders throughout the company.

As a senior data scientist, you are expecting to:

In order to be successful for this role, we are looking for:

It will be a plus if you also have:

Excited by this opportunity? We invite you to apply now and start the conversation with us. Together, we can create and support some of the best games ever made and entertain the world!

About Kabam

Kabam is a world leader in developing entertaining, immersive, and highly social multiplayer games, bringing high-quality graphics, next-generation technology, and revolutionary gameplay to players around the world.

Kabam’s games, Marvel Contest of Champions, Disney Mirrorverse, Shop Titans, and Transformers: Forged to Fight, have generated hundreds of millions of downloads and have received multiple awards including Apple’s Editor’s Choice and Google Play’s Best Game of the Year.

Founded in 2006, Kabam has studios and offices in North America, including Vancouver and Montreal in Canada, and Los Angeles and San Francisco in the United States. Kabam is a wholly-owned subsidiary of Netmarble Games.

Kabam is an Equal Employment Opportunity employer committed to building a diverse and equitable workplace, and inclusive environment for all existing and potential employees. Employment decisions are based on candidate qualifications and business need, not race, color, ancestry, place of origin, age, sex (including pregnancy), gender identity or expression, sexual orientation, political belief, religion, creed, marital or family status, medical condition, genetic information, physical or mental disability, military or veteran status, prior criminal conviction or any other protected class in accordance with federal, state or provincial and local laws and ordinances. Accommodations will be provided as requested by candidates taking part in all aspects of the selection process.

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