At Playlist, life's richest moments happen when people step away from screens to move, connect, explore, and play. We're building the definitive platform for intentional living, connecting people with inspiring experiences in fitness, wellness, and beyond. With popular brands like Mindbody and ClassPass, Playlist empowers businesses and individuals, making it effortless for aspirations to become actions. Join us in reshaping technology's role to foster meaningful, real-world connections.
Mindbody equips wellness entrepreneurs with technology to support thriving businesses and create exceptional experiences. Innovation and curiosity drive our culture, connecting businesses and individuals through cutting-edge solutions. Join us if you're passionate about enhancing wellness through technology.
As a Data Scientist, you will play a critical role in driving insights and building data products that support large-scale, cross-departmental initiatives. You'll combine advanced statistical inference, strong engineering skills, and business intuition to create models and tools that improve marketplace efficiency, retention, and growth. This role is not about building models in isolation--it's about leveraging data science to influence strategy, fuel automation, and deliver measurable business impact.
Partner with Product, Marketing, Operations, and Finance teams to design and execute analytical solutions that optimize marketplace dynamics, improve unit economics, and uncover opportunities for growth.
Apply statistical inference and causal modeling to evaluate experiments, quantify business impact, and guide decision-making under uncertainty.
Design, prototype, and deploy scalable data products such as anomaly detection systems, prioritization algorithms, and similarity/recommendation models.
Translate complex models and findings into actionable insights and clear recommendations for business stakeholders, including executives.
Build frameworks for experimentation, measurement, and monitoring that drive iteration and continuous improvement of strategic initiatives.
Balance hands-on technical work (modeling, coding, automation) with strategic thinking, ensuring data science investments align with business objectives.
Act as a technical thought partner and mentor for analysts and junior data scientists, raising the bar on scientific rigor and reproducibility.
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