Business Intelligence ofertas em Espanha

PENN Entertainment, Inc. is North America’s leading provider of integrated entertainment, sports content, and casino gaming experiences. From casinos and racetracks to online gaming, sports betting and entertainment content, we deliver the experiences people want, how and where they want them.

We’re always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether it’s through ESPN BET, Hollywood Casino, theScore Bet Sportsbook & Casino, or theScore media app, we’re excited to push the boundaries of what’s possible. These state-of-the-art platforms are powered by proprietary in-house technology, a key component of PENN’s omnichannel gaming and entertainment strategy.

When you join PENN Entertainment’s digital team, you’ll not only work on these cutting-edge platforms through theScore and PENN Interactive, but you’ll also be part of a company that truly cares about your career growth. We’re committed to supporting you as you expand your skills and explore new opportunities.

With locations throughout North America, you can build a future at PENN Entertainment wherever you are. If you want to challenge conventions in gaming, media and entertainment, we want to talk to you.

The Machine Learning Platform team at Penn Entertainment is dedicated to building and maintaining the infrastructure, tools, and frameworks that support our data science and machine learning initiatives. As the Engineering Manager of the ML Platform, you will lead a team of talented engineers, fostering a culture of collaboration, innovation, and technical excellence. You will be responsible for guiding the team in developing scalable machine learning platforms, optimizing model deployment processes, and implementing best practices in machine learning operations (MLOps).

• Drive the vision, strategy, and execution of the machine learning platform, ensuring alignment with data science and machine learning deliverables at the company.
• Hire, mentor, and lead a team of ML platform engineers, fostering professional growth and a culture of innovation.
• Oversee the development of scalable ML infrastructure, model serving, feature stores, and monitoring systems.
• Partner with stakeholders across data engineering, ML engineering, and data product teams to enable the development of robust ML pipelines and integrations.
• Establish and improve MLOps best practices, ensuring robust CI/CD pipelines, model monitoring, and efficient resource utilization.
• Assess and recommend new tools, frameworks, and technologies to improve the efficiency and effectiveness of machine learning solutions.
• Maintain technical design documents, Git/Confluence documentation, and ensure knowledge sharing across the team.

• Experience: 3+ years of professional experience in machine learning, data engineering, or software engineering, with at least 2 years in a leadership or managerial role.
• Strong background in machine learning infrastructure, data engineering, and software development, with proficiency in Python, SQL, and cloud platforms (GCP, AWS, Azure).
• Experience with machine learning packaging and serving patterns and related tooling (MLflow, Seldon, Kserve, Vertex, AWS SageMaker).
• Hands-on experience with CI/CD pipelines, containerization (Docker, Kubernetes), and orchestration tools (Airflow, Kubeflow, or Dagster).
• Ability to communicate complex technical concepts to non-technical stakeholders and lead a high-performing team.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

• Experience with real-time stream processing and virtual feature stores (Featureform, Feast).
• Background in deploying and monitoring large language models (LLMs).
• Familiarity with BI tools such as Tableau, Looker, or Mode.

Candidates residing in Ontario requiring special accommodation can email accessibilityoffice@thescore.com

theScore is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability or age.