Principal Machine Learning and Data Science Engineer

4 weeks ago

Grapevine, United States GameStop Full time

At GameStop, we are committed to providing exceptional service and delivering the latest and greatest in gaming products to our customers. As a leading global retailer of video games, electronics, and gaming merchandise, we take pride in offering a wide range of products that cater to the needs and desires of gamers worldwide. Our mission is to create unforgettable experiences for our customers by constantly pushing the boundaries of what's possible. Whether you're a hardcore gamer or just starting out, we've got something for everyone. Join us in our mission to shape the future of gaming and bring the best gaming products to the world

We are seeking a highly skilled and experienced Principal Machine Learning and Data Science Engineer to join our dynamic and passionate team. The ideal candidate will be responsible for developing and deploying advanced machine learning models, leading data science initiatives, and collaborating with cross-functional teams to drive business objectives, strategic goals, and enhance the personalized gaming and collectibles shopping experience.
 

This position will sit onsite in Grapevine, TX.
 

Key Responsibilities:

  • Design, develop, and implement machine learning algorithms and models to solve complex business problems, optimize inventory management, and enhance product recommendations in the gaming and collectibles ecosystem.
  • Lead end-to-end data science projects, from data collection and preprocessing to model development, validation, and deployment, focusing on gaming trends, collectibles valuation, and market demand forecasting.
  • Collaborate with cross-functional teams, including software engineers, data engineers, product managers, and collectibles experts, to integrate machine learning models into GameStop's digital platforms, services, and customer experiences.
  • Evaluate and improve the performance of existing machine learning models through continuous monitoring, optimization, and retraining, ensuring accurate collectibles pricing, gaming recommendations, and personalized shopping experiences.
  • Conduct exploratory data analysis to identify patterns, trends, and insights that can inform business decisions, marketing strategies, collectibles valuation, and personalized gaming recommendations.
  • Utilize Google Cloud Platform (GCP) services and tools for data storage, processing, and machine learning model deployment, leveraging Google Cloud AI/ML services, BigQuery, Dataflow, and other GCP services to build scalable and efficient data science solutions.
  • Stay current with the latest advancements in machine learning, data science, gaming technologies, collectibles market trends, and related industries to ensure GameStop's solutions remain cutting-edge, innovative, and competitive.
  • Mentor and guide junior data scientists and engineers, fostering a culture of innovation, collaboration, and excellence within GameStop's data science, engineering, and collectibles teams.
     

Qualifications:

  • Master’s or Ph.D. degree in Computer Science, Data Science, Statistics, or a related field.
  • Minimum of 5 years of professional experience in machine learning, data science, and software engineering.
  • Strong proficiency in programming languages such as Python, R, or Java, and familiarity with machine learning libraries/frameworks like TensorFlow, scikit-learn, etc.
  • Solid understanding of statistical analysis, experimental design, and data visualization techniques.
  • Hands-on experience with Google Cloud Platform (GCP) services and tools.
  • Passion for gaming, collectibles, and a deep understanding of the gaming industry trends, collectibles market, player behaviors, and gaming platforms.
  • Excellent problem-solving skills, with a keen attention to detail and a passion for continuous learning and improvement.
  • Strong communication and interpersonal skills, with the ability to effectively collaborate with team members at all levels of the organization, including collectibles experts and enthusiasts.

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