Data Scientist, Machine Learning at Orlando Magic
Job Description
Before we get into the specifics of the role, there are a few things we want you to know:
At the Orlando Magic, our approach is to not only learn as much about you as we can, but for you to learn about us. This is definitely a two-way street, so time with your potential new leader, teammates, and/or other departments that the role will work with is critical. It isn’t just, “what are we looking for”, but also, “what do we have to offer you” and “are we the right fit for you.” While every position is different, our interview process is typically a three-step process, sometimes more depending on the level and nature of the role.
What we offer you:
- Staff tickets to Magic home games, learning and development opportunities, Employee Resource Groups (ERGs), company sponsored events, volunteer opportunities & outings for every employee.
- Fantastic benefits that include: medical, dental, vision, 401(k) with company matching, mental wellness resources, subsidized gym memberships, maternity & paternity leave.
- Culture built on Community, Innovation, Legendary and Teamwork!
A quick summary about the Data Scientist, Machine Learning:
The Data Scientist, Machine Learning will support Basketball Operations by developing and deploying machine learning models to inform decision making across player evaluation, game strategy, and player development. This role will own key parts of the model development lifecycle, from experimentation and training to production deployment, with a focus on spatiotemporal modeling, scalable data pipelines, and reliable model delivery. This is an in-person opportunity in Orlando, FL.
What the Data Scientist, Machine Learning will do:
- Build and productionize machine learning models that support basketball decision making.
- Design and maintain scalable systems and pipelines for data processing, training, inference, and monitoring.
- Partner closely with analysts, engineers, and basketball stakeholders to turn research ideas into reliable tools.
- Establish best practices for testing, validation, documentation, versioning, and model observability.
- Develop modeling approaches that translate basketball data into clear, actionable insights.
- All other duties as assigned.
What the Data Scientist, Machine Learning needs to have:
- Bachelor’s in Computer Science, Statistics, Math or related field.
- 1+ years of experience with Python and SQL, with solid software engineering fundamentals including testing, version control, and maintainable code practices.
- 1+ years of experience with applied machine learning techniques, with fluency across tree-based methods, deep learning, and modern modeling workflows.
- 1+ years of experience with building, deploying, and maintaining end to end machine learning systems in production environments.
- Passion for basketball and an understanding of the basketball analytics space.
- Willingness to work long and irregular hours with a flexible schedule based on the changing priorities of the department.
- Willingness to work a flexible schedule including nights and weekends and be on-call as necessary based on the changing priorities of the department.
- Proficient in all Microsoft Office products and other related computer skills required.
- Ability to meet tight deadlines and work well under pressure.
- Strong organizational skills, time management skills and attention to detail required.
- Strong verbal and written communication skills with an emphasis on business writing skills.
- Ability to prioritize and manage multiple tasks/projects.
- Ability to work independently without supervision, be self-directed and demonstrate initiative.
- Strong team synergy skills and ability to work collaboratively with others whom you have no direct authority over.
- Excellent ability to establish rapport with others and ability to build strong interpersonal relationships.
- Exhibit good judgment and decision-making skills.
Physical requirements
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None
If this opportunity is a role you're passionate about and it fits with your skills and experience, then we welcome you to take the next step and apply!
All offers of employment are contingent on successful completion of our pre-employment screenings, that will include a background check and may include a drug screen.
Please note that this is not necessarily an exhaustive list of all responsibilities, duties, skills, efforts, requirements or working conditions associated with the job. While this is intended to be an accurate reflection of the current job, management reserves the right to revise the job or to require that other or different tasks be performed as assigned.
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