The Data Scientist will develop and operationalize machine learning (ML) models as part of our behavioral machine learning initiatives. You will be responsible for:
• Building scalable machine learning models to detect and provide context around disruptive behavior.
• Designing and maintaining scalable, efficient, production-quality detection tools to inform operations and measure performance.
• Researching and implementing novel ML approaches for new problems.
• Translating requirements from cross-disciplinary teams in Game Operations, Marketing, CRM, and Business Planning into data solutions.
• Synthesizing disparate data, detecting and working around broken data, and investigating every possibility until you have a thorough solution.
• Surfacing and communicating results to technical and non-technical colleagues by generating dashboards and reports.
As a machine learning expert on the team, you will leverage your experience to steer data-driven discussions, improve internal processes, and communicate results to technical and non-technical colleagues. You will be a trusted member of an established team of data scientists and machine learning engineers, focused on ensuring player satisfaction in our games. You will accomplish this by:
• Being a tenacious and self-catalyzing problem solver.
• Driving towards visibility, accountability, and communication.
• Being team-oriented, and able to build long-lasting and collaborative relationships effectively.
• Respectfully contributing your professional experience in every conversation.
• Listening with openness to others.
• Adapting quickly, having a high tolerance for ambiguity, and coordinating effectively on a team.
• Evangelizing ethical ML by being thoughtful about identifying, testing for, and reducing biases in models.
• M.S. in Mathematics, Machine Learning, Data Science, Statistics, Operations Research, Economics, or other quantitative field.
• 3+ years experience as a data scientist. Senior level depends on additional experience.
• NLP experience, including TF-IDF, text normalization, word embedding, and LSTM
• General machine learning experience, i.e. regression, classification, and clustering algorithms, time-series analysis, Bayesian methods, and survival analysis.
• Prototype-to-production engineering skills in Python, including best practices such as source control, proper documentation, library packaging, versioning, testing, containerization, CI/CD, and task scheduling.
• Advanced SQL and Spark skills.
• Professional habits around model validation, testing, and tracking.
• Solid understanding of statistics, e.g. statistical power analysis, significance testing, t-tests, ANOVA.
• Engineering experience in at least one cloud platform such as AWS, GCP, or Azure.
• Ph.D. with peer-reviewed publications and a proven track record of self-guided research.
• Video game enthusiasm with a solid understanding of the gameplay mechanics in Warzone.
• Exposure to stream processing infrastructure such as Kafka and Spark Streaming.
• Hardware-level knowledge (C++, memory management, GPU rendering).
Jobcode: Reference SBJ-g3x7n9-54-144-55-253-42 in your application.