Sr Applied Scientist
On-siteDublin, Leinster, Ireland
Job Summary
Sr Applied Scientist for the Applied AI Team focused on NBA 2K. Design, develop, and iterate machine learning models that impact in-game experiences and core systems such as matchmaking, skill rating, and recommender systems. Build and refine representation learning models to capture player skill, lineup/build strength, and interaction patterns from sequential gameplay data. Stay informed on state-of-the-art techniques, evaluate applicability, and lead efforts to integrate promising methods into production. Formulate ambiguous product problems into well-defined ML tasks; lead technical discussions, advocate best practices, and ensure scientific rigor. Collaborate with engineers, MLEs, and product stakeholders to integrate models into production systems and influence game design decisions.
Required Qualifications
- Master’s or Ph.D. in a quantitative field (Mathematics, Statistics, Physics, Computer Science, Operations Research, Industrial Engineering, Electrical Engineering).
- Proven experience in applied science, machine learning, or data science roles, including experience deploying ML models in production environments.
- Proven experience with deep learning, representation learning, embedding models, or self-/semi-supervised learning.
- Fluency in Python and SQL (or similar scripting languages). Experience with big data technologies such as Apache Spark.
- Working knowledge of machine learning modeling/computation frameworks such as PyTorch or Tensorflow.
- Demonstrated ability to work independently, rapidly prototype solutions, and test new ideas.
- Strong communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
- Experience with recommendation systems, ranking systems, or user behavior modeling.
- Experience with sequence models (e.g., RNNs, Transformers), graph-based approaches, or autoencoders.
- Familiarity with cloud services (such as AWS), containerization, model orchestration, and model serving.
- Familiarity with sports analytics, sports predictive modeling, or NBA domain knowledge is a plus.
- Interest in understanding video games as products.
Desired Qualifications
- Experience with recommendation systems, ranking systems, or user behavior modeling
- Experience with sequence models (RNNs, Transformers), graph-based approaches, or autoencoders
- Familiarity with cloud services (AWS), containerization, model orchestration, and model serving
- Familiarity with sports analytics, sports predictive modeling, or NBA domain knowledge
- Interest in understanding video games as products
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