Senior Manager, Data Science & Analytics at NCSA College Recruiting

About NCSA College Recruiting NCSA College Recruiting is the world largest college recruiting platform, providing student-athletes content, tools, coaching and access to a network of 40,000 college coaches across 37 sports. NCSA is an online experience of IMG Academy, the world’s leading sports education brand and one of the Best and Brightest Companies to Work For in the Nation in 2024 and Top Remote Places to Work in 2024. IMG Academy provides a holistic education model that empowers student-athletes to win their future, preparing them for college and for life. Additional on-campus and online experiences include: • Boarding school and camps, via a state-of-the-art campus in Bradenton, Fla. • Online coaching via IMG Academy+, with a focus on personal development through the lens of sport and performance Position Summary: The Senior Manager, Data Science & Analytics, is responsible for building and leading a high-impact analytics and data science organization. This role blends strategic leadership, technical depth, and people management, partnering closely with Product, Marketing, Technology, and Business leaders to turn data into insights, models, and product capabilities that drive growth. The Senior Manager will define the operating model for Data Science & Analytics, set standards and priorities, and develop leaders within the function while remaining technically fluent enough to guide complex analytical and machine learning work. Position Responsibilities: Leadership & Team Development • Lead and manage a team comprised of a data science manager, data scientists and analysts at various levels • Hire, onboard, and develop talent; create clear career paths and progression frameworks. • Coach managers and senior ICs on technical excellence, prioritization, and stakeholder management. • Foster a culture of accountability, collaboration, experimentation, and continuous learning. • Establish performance expectations and conduct regular feedback, reviews, and development planning. • Set analytical standards, best practices, and reusable frameworks across the team. • Partner across functions and align stakeholders around data-driven outcomes. Advanced Analytics • Lead the design and development of advanced analytics and machine learning models to support business, product, and customer initiatives. • Apply statistical modeling, predictive analytics, experimentation, and causal inference to solve complex business problems. • Translate ambiguous business questions into well-defined analytical problems and deliver clear, actionable insights. Machine Learning • Design, build, and deploy machine learning models embedded directly within products, including recommender systems, ranking models, personalization engines, and predictive features. • Build, deploy, and maintain machine learning models in production, including model monitoring, evaluation, and ongoing optimization. • Partner closely with product and engineering teams to integrate ML models into user-facing experiences and backend systems. • Identify opportunities where ML can drive automation, personalization, forecasting, and optimization within products and customer journeys. Customer Analytics & CDP • Lead customer analytics initiatives, including segmentation, lifecycle analysis, attribution, personalization, and retention modeling. • Leverage and help mature the organization’s Customer Data Platform (CDP) to enable unified customer views and data-driven decision-making. • Partner with Marketing and Growth teams to support targeting, experimentation, and measurement. Product Analytics • Partner with Product teams to define success metrics, build dashboards, and perform deep-dive analyses to inform roadmap and prioritizations. • Establish best practices for product experimentation (A/B testing), funnel analysis, and feature performance measurement. • Enable data-informed product decisions through storytelling and clear communication. Knowledge, Skills and Abilities: • 8+ years of experience in data science, analytics, or a related field, with increasing scope and responsibility. • Demonstrated experience managing and developing analysts and/or data scientists. • Strong foundation in statistics, probability, and experimental design. • Demonstrated experience building and deploying machine learning models. • Proficiency with statistical programming languages (Python or R) • Proficiency with SQL and experience with data visualization tools (Tableau, Power BI, et al.) • Hands-on experience with customer analytics, CDPs, and/or marketing data ecosystems. • Proven ability to influence stakeholders and translate data into business impact. • Experience mentoring or managing analysts or data scientists (formal or informal leadership). Background Requirements: • Requires a background check upon offer Benefits: ...