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Data Scientist
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Data Scientist
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Data Scientist
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Data Scientist
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About
Cavaliers Holdings LLC is obsessed with delivering epic experiences for our team members, our fans, our community and the world. Fueled by an unapologetically bold, inclusive and high-impact culture, we strive to recruit individuals who are enthusiastic and purposeful in carrying out our vision as transformative leaders in sports and entertainment If you are ready to bring your best to the dynamic, high‑performance environment of the Cavs, Cleveland WNBA, Monsters, Charge, RESN and Rocket Arena - where we come together to create moments that move, inspire and uplift - then we want to hear from you. The Business Intelligence team is seeking a highly motivated data scientist to assist with collecting, analyzing, and presenting data insights. The role will use statistical methods and advanced analytics to inform key strategic initiatives. Specific initiatives will be derived from cross-functional business needs. You'll dive deep into the numbers behind ticket sales, corporate partnerships and even the food and merchandise fans love to get during the big game. Your insights will directly impact key decisions that shape the future of our organization. Essential Duties & Responsibilities: Meet with business stakeholders to determine analytic needs. Develop and execute statistical modeling techniques to generate insights. Independently extract, join and preprocess necessary data from disparate data streams. Support the execution and interpretation of machine learning models. Identify areas of opportunity to improve existing analytic support. Provide decision support through ad-hoc analysis and scenario modeling. Maintain an understanding of the latest trends and technologies related to data science. Required Qualifications: Bachelor's Degree in a quantitative field (Math, Stats, Analytics, Engineering, Economics, etc.). 1+ years of relevant professional experience in data science. Foundational knowledge of supervised/unsupervised learning (regression, classification, clustering) and evaluation metrics. Comfort with applied statistical modeling. Ability to effectively communicate with both technical and business-minded professionals. Ability to manage multiple priorities and work independently. Proficient in data analysis tools and programming languages (e.g. SQL, R, Python). We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.
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