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Applied Scientist

2K -
Dublin, County Dublin

Quick apply

Job details

20 hours ago

Qualifications

TensorFlow
Doctoral degree
Big data
Spark
Master's degree
SQL
AWS
Scripting
Predictive analytics
Communication skills
Python
Analytics

Full job description

Who We Are

At 2K, we create some of the most iconic and culture-shaping video games in entertainment, including NBA® 2K, one of the top-selling franchises in the world, and legendary titles like BioShock®, Borderlands®, Mafia, Sid Meier's Civilization®, and XCOM®, as well as fan favorites WWE® 2K, TopSpin®, and PGA TOUR® 2K. We build unforgettable experiences by pushing the boundaries of creativity, authenticity and innovation across every genre.

Our portfolio is brought to life by some of the most influential game development studios in the world. Visual Concepts, Firaxis Games, Hangar 13, Cat Daddy Games, 31st Union, Cloud Chamber, Gearbox, HB Studios, and 2K SportsLab create world-class experiences across platforms.

But what truly powers 2K is our people.

We believe the best ideas come from teams that feel empowered, supported, and inspired. As an equal opportunity employer, we are committed to fostering a diverse, inclusive workplace where people are encouraged to come as they are and do their best work.

What We Need

2K is looking for a Sr. Applied Scientist to join the Applied AI Team in the Product Organization, with a focus on our flagship franchise NBA 2K. Our team leverages AI, machine learning, statistics, and operations research, and economics to build systems that power core game experiences. We develop algorithmic solutions in areas such as matchmaking, in-game experience personalization, player engagement, in-game economy, content optimization, and fraud detection.

What You'll Do

Design, develop, and iterate on machine learning models that directly impact in-game experiences and core systems (e.g., matchmaking, skill rating systems, 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 their applicability, and lead efforts to integrate promising methods into our systems.
Formulate ambiguous product problems into well-defined machine learning tasks.
Lead technical discussions, advocate for best practices in model development and deployment, and ensure scientific rigor.
Collaborate closely with engineers, MLEs, and product stakeholders to integrate models into production systems and influence game design decisions.

What Will Make You A Great Fit

We are seeking a senior scientist with strong foundations in machine learning and statistics, combined with hands-on experience building and applying models to real-world problems. The ideal candidate is comfortable working with imperfect data, defining problems from scratch, and applying modern modeling approaches—including deep learning and representation learning—to generate meaningful impact.

They should be a curious, solution-oriented problem solver who can move between research ideas and practical implementation, and who takes ownership of their work end-to-end.

Requirements:

Master's or Ph.D. in a quantitative field (Mathematics, Statistics, Physics, Computer Science, Operations Research, Industrial Engineering, Electrical Engineering).
4+ years of 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.

Preferred Qualifications (Helpful, but Not Required):

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.

As an equal opportunity employer, we are committed to ensuring that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform their essential job functions, and to receive other benefits and privileges of employment. Please contact us if you need reasonable accommodation.

Please note that 2K Games and its studios never uses instant messaging apps or personal email accounts to contact prospective employees or conduct interviews and when emailing, only use 2K.com accounts.

#LI-Hybrid

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