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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