Data Scientist

• Own the end-to-end design, development, and production deployment of advanced AI and data-driven solutions
• Build scalable machine-learning models with large, heterogeneous datasets to solve complex business challenges
• Provide proactive, data-driven guidance to our Customer Success organization
• Collaborate with customer success, product, engineering, and sales teams to define KPIs and analytical approaches that answer key business questions
• Design, build, and deploy machine learning and AI models (classification, regression, NLP, recommendation engines, etc.) to identify at-risk customers, predict attrition, and assess impact of product offerings
• Develop customized recommendation engines that suggest next-best actions for customers (collaborative filtering, content-based, hybrid, graph-based techniques, etc.)
• Drive the end-to-end machine learning lifecycle, from data preprocessing and feature engineering to model training, testing, and automated retraining workflows
• Architect high-performance data pipeline for massive, multi-source datasets (streaming, batch, semi-structured), ensuring optimal storage, fast query performance, and high data integrity in hybrid cloud environments
• Monitor production model performance by tracking key metrics like accuracy, drift, and latency
• Leverage A/B testing and establish feedback loops to drive continuous improvement and rapid iteration
• Support translation of strategic direction into analytical problems and actionable data science initiatives, ensuring data science alignment with organizational goals and long-term vision
• Present clear, actionable insights and technical roadmaps to technical and non-technical stakeholders at all levels.

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