Job Description

Company Description
At Maple Leaf Sports & Entertainment Partnership (MLSE), we are committed to creating an inclusive workplace that is representative of our community and where all employees feel they belong and can reach their full potential. We are Canada\xe2\x80\x99s preeminent leader in delivering top quality sport and entertainment experiences and one of North America\xe2\x80\x99s leading providers of exceptional fan experiences. We are the parent company of the National Hockey League\xe2\x80\x99s Toronto Maple Leafs, the National Basketball Association\xe2\x80\x99s Toronto Raptors, Major League Soccer\xe2\x80\x99s Toronto FC, the Canadian Football League\xe2\x80\x99s Toronto Argonauts and development teams with the Toronto Marlies (American Hockey League), Raptors 905 (NBA G League), Toronto FC II (MLS NEXT Pro League) and Raptors Uprising Gaming Club, the Toronto Raptors Esports franchise in the NBA 2K League.

MLSE owns and/or operates all the venues our teams play and train in, including Scotiabank Arena, BMO Field, Coca-Cola Coliseum, Ford Performance Centre, BMO Training Ground, and OVO Athletic Centre. We also provide fans in Toronto with incredible live music and entertainment events, as well as exceptional culinary experiences through our restaurants (e11even and RS) and clubs (Hot Stove Club, ScotiaClub and Platinum Club). Through MLSE Foundation, we have invested more than $45 million into Ontario communities since 2009 and with MLSE LaunchPad, we provide a place where youth facing barriers use sport to recognize and reach their potential.

We achieve all of this through our Common Purpose - to unite and empower our employees to create extraordinary moments for our fans and each other. Come be a part of the team.


Reporting to the Director, Business Analytics, the Machine Learning Engineer will have the unique opportunity to contribute to the research, analysis and business process development related to MLSE\xe2\x80\x99s Fans and customers and provide insights to build fan experiences. Primarily, the candidate will work hand in hand with the Analytics team and business collaborators within the firm to develop and maintain data pipelines to improve workflows and automate processes wherever possible. The ideal candidate has a passion for data, a strong background in data engineering, database management, a curiosity about Machine Learning. Responsibilities:

• Oversee the design and maintenance of data pipelines and contribute to the continual improvement of the data engineering architecture.
• Collaborate with the team to meet performance, scalability, and reliability goals.
• Write out tests and detailed documentation for processes and tooling.
• Adapt to working with new technologies and frameworks, sometimes headlining the investigation into their usefulness to the team.
• Maintain and expand existing systems, tooling and infrastructure.
• Maintain the data warehouse ensuring data integrity and performance.
• Support the development of KPIs and benchmarks for new strategic initiatives.
• Research into and report on sports & entertainment industry standard processes.
• Facilitate and collaborate with key business stakeholders to identify business requirements and translate these to technical documentation.
• Work in compliance with provisions of the Occupational Health & Safety Act.
• Follow all MLSE Health & Safety policies and procedures.
• Perform other administrative or service functions as the need arises.

Qualifications
Note: Before reviewing the qualifications listed below, we want you to know that we understand you may not meet all the qualifications described and have other relevant expertise and experience. We invite you to please share this with us in the "Message to the Hiring Manager" section of our online application.

• 
  A strong background in Python/Spark, knowledge of Databricks, AWS.
• Proven experience as a Machine Learning Engineer/Data Engineer or similar role.
• Experience with data preparation and transformations, ETL development, data modeling, data warehousing, and databases in a business environment with large-scale, complex datasets.
• Knowledge of conceptual modelling, metadata, reference data management, data quality and analysis.
• Understanding of data structures, data modeling and software architecture.
• Technical expertise with data models, data mining, and segmentation techniques.
• Hands-on experience with SQL database design.
• Great numerical and analytical skills.
• Ability to write robust code in Python.
• Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn, Pandas, NumPy).
• Proficient with Microsoft Office products including Excel, PowerPoint, and Word.
• Strong communication, organizational and interpersonal skills.
• Team first, people-oriented, and energetic attitude.
• Previous experience in building ML models is a plus.
• Visualization experience in Power BI or Tableau is a plus
• BSc in Computer Science, Mathematics or similar field; Master\xe2\x80\x99s degree is a plus or equivalent experience.
• an interest in professional sports and/or eSports is a plus.
• Available to work full-time regular hours with flexibility around event-based work.

Additional Information
Apply by: February 17, 2023 We thank all applicants for their interest, however, only those selected for an interview will be contacted. At MLSE, we are committed to building an equitable, diverse and inclusive organization. We are an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. MLSE will provide reasonable accommodation for qualified individuals with disabilities in the job application process. If you have difficulty using our online application system and you need an accommodation due to a disability, please email accommodations@mlse.com. Please note this email is only for accommodation requests. Resumes sent to this email address will not be considered.