Charter Solutions is hiring a Data Scientist locally in the Minneapolis area.
Key Responsibilities
- Lead the development and execution of the data science strategy focused on audience engagement, subscriber growth, content optimization, and personalization initiatives.
- Design, develop, deploy, and maintain recommendation and personalization solutions throughout the full machine learning lifecycle.
- Own production machine learning models, including deployment, monitoring, performance optimization, retraining, and support for near real-time prediction capabilities.
- Conduct statistical analyses, predictive modeling, and experimentation to generate actionable insights that drive product enhancements and business outcomes.
- Define and promote best practices for experimentation, model validation, reproducibility, machine learning governance, and deployment processes.
- Collaborate with Data Engineering and Cloud Engineering teams to ensure reliable access to data and scalable infrastructure for analytics and machine learning workloads.
- Present complex analytical findings and recommendations in a clear, business-focused manner to product, editorial, and executive stakeholders.
Qualifications
- Proven experience as a Data Scientist with a strong track record of building, deploying, and supporting recommendation or personalization engines in production environments.
- Deep expertise in applied statistics, experimental design, machine learning, and predictive analytics.
- Experience with MLOps practices, including model deployment, monitoring, maintenance, and near real-time inference, is highly desirable.
- Advanced SQL skills and proficiency with modern data platforms and analytics tools, including Snowflake and business intelligence solutions such as Domo.
- Demonstrated ability to provide technical leadership and analytical direction while remaining actively involved in hands-on development and delivery.
- Excellent communication skills with the ability to translate technical concepts and insights into meaningful business recommendations for non-technical audiences.
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