Boston Red Sox - Data Scientist, Baseball Analytics
Requirements
• PhD or master's degree in a quantitative field (such as statistics, engineering, applied mathematics, physics, quantitative social sciences, computer science, computer vision, or operations research) or equivalent professional experience. • Proficiency in SQL and programming languages such as R or Python. • A passion for baseball and a strong desire to contribute to building a championship-winning team. • In addition to the above requirements, all roles within Baseball Operations are expected to effectively demonstrate our universal competencies related to problem solving, teamwork, clarity of communication, and time management, along with embodying our culture of honesty, humility, relentlessness, and commitment to DEIB. • At the Boston Red Sox we go beyond embracing diversity. We’re committed to living by our values, strengthening our community, and creating a workplace where people genuinely feel like they belong. • Too often, job seekers don’t apply to positions because they don’t meet every qualification. If you love this role and are great at what you do, we encourage you to apply. Your unique skills and experiences might just be what we’ve been looking for. • Prospective employees will receive consideration without discrimination based on race, religious creed, color, sex, age, national origin, handicap, disability, military/veteran status, ancestry, sexual orientation, gender identity/expression or protected genetic information.
Responsibilities
• Design and maintain robust predictive models and data pipelines to generate insights for player evaluation, acquisition, development, and performance optimization. • Craft compelling written reports and data visualizations to effectively communicate complex analyses to diverse audiences, including both technical specialists and Baseball Operations leadership. • Partner with the Baseball Systems team to seamlessly integrate new analytical findings into team applications and proactively identify and address data quality issues. • Continuously monitor and evaluate cutting-edge analytics and research from public and academic spaces to recommend innovative ideas, methodologies, and technologies that can enhance on-field performance. • Understanding of modern statistical and machine learning methods and an advanced proficiency with popular data science languages and libraries. • Practical understanding of how to approach research questions to drive actionable insights. • Able to visualize, present and disseminate analyses to a diverse group of stakeholders (leadership, coaches, players, scouts, etc.) in a clean, intuitive, and engaging way.
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