The data scientist utilizes machine learning to change the way we make and operate our world-class games. You will drive the design and implementation of end-to-end machine learning systems for production. The data scientist will work within the data science and analytics department; a centralized department that works with stakeholders throughout the company.
As a data scientist, you are expecting to:
- Help to identify opportunities for machine learning in our products
- Own a machine learning system
- Query our petabyte-scale database to extract game data
- Conduct exploratory data analysis, hypothesis testing, and feature engineering
- Build and evaluate machine learning models to improve in-game features and boost product metrics
- Communicate project goals, progress, and outcomes with production, design, and engineering teams
- Perform tests to evaluate the ROI/lift of machine learning models
- Work with engineers to deploy models (batch predictions, microservices, and monitoring)
In order to be successful for this role, we are looking for:
- Master’s Degree in a STEM discipline, preferably thesis-based
- 2+ years of industry experience in data science, preferably in large scale client-facing software/web/application companies
- Professional level Python programming skills (NumPy, pandas)
- Experience deploying machine learning models into production
- Proficient with machine learning libraries: eg. sci-kit-learn, TensorFlow, PyTorch
- Strong SQL skills (joins, subqueries, analytic functions)
- Can drive projects independently, maneuver through imperfect data or experimentation, and pivot goals or targets with ease
- Communicates in a clear, concise, and professional manner with staff at all levels; justifies decisions, and achieves peer consent
It will be a plus if you also have:
- Software/ML or data engineering experience
- PhD in a STEM discipline
- Proficient in Docker, Airflow, Bigquery, Tableau, Github
- Game industry experience
- Experience with Pytorch, Tensorflow, Other Deep Learning Libraries
- Experience with recommendation systems
- Background in advanced statistics
- Experience working with Google Cloud Platform, or other cloud-based machine learning platform
- Evidence of continued learning
- Active Github or Kaggle Profile
Together, we can create and support some of the best games ever made.
About Kabam
Kabam is a world leader of developing entertaining, immersive, and highly social multiplayer games for mobile devices. They merge consumer behaviour with the art of game design to create experiences that are enjoyed by millions of players across the globe. Each game has raised the benchmark in mobile gaming, bringing high-quality graphics, next-generation technology and revolutionary gameplay to the console in every player’s pocket.
Kabam has partnered with leading entertainment brands like Disney, Hasbro and Universal to create mobile games based on some of the world’s most iconic franchises.
Kabam’s games have generated hundreds of millions of downloads including Fast & Furious 6: The Game, Fast & Furious: Legacy, Marvel Contest of Champions, Transformers: Forged to Fight, Shop Titans and Mini Guns. These games have also received multiple awards such as Apple’s Editor’s Choice and Google Play’s Best Game of the Year.
Founded in 2006, Kabam has studios and offices in Vancouver, Montreal, Charlottetown, San Francisco and Austin. 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.
