Description
• Lead the strategic direction and execution of data science initiatives for Risepoint's innovative Student Journey Platform, a system designed to proactively understand and address student needs.
• Drive the development and implementation of cutting-edge machine learning models, overseeing their entire lifecycle from initial discovery and development through to production deployment, ongoing governance, and continuous monitoring.
• Architect and build robust frameworks for extracting high-signal insights from diverse data sources, including voice, text, and behavioral interactions, leveraging both classical Natural Language Processing (NLP) techniques and advanced Large Language Models (LLMs) and generative AI.
• Integrate disparate data signals to construct a unified, real-time view of student intent and overall experience, enabling personalized interventions and support.
• Spearhead the technical product analytics and experimentation roadmap, employing rigorous statistical methods such as A/B testing, feature rollouts, and behavioral studies to ensure AI-powered product decisions are data-driven.
• Define and implement stringent evaluation standards for both generative and predictive AI features, ensuring their accuracy, reliability, and effectiveness in real-world applications.
• Foster a culture of ownership, analytical rigor, and rapid iteration within a multidisciplinary data science team, promoting technical excellence and continuous improvement.
• Collaborate closely with Product Management and Engineering teams to define key technical success metrics that directly translate into measurable business Return on Investment (ROI).
• Translate complex technical concepts, model outcomes, and analytical findings into clear, compelling narratives for executive leadership, driving alignment and facilitating strategic decision-making.
• Ensure the predictive precision of models, enabling them to accurately anticipate student needs, trigger timely interventions, and demonstrably improve with each interaction.
• Transform conversational data (voice and text) into a strategic asset, establishing it as a structured, queryable source of truth that informs product development and operational strategies.
• Implement a comprehensive AI evaluation and monitoring program for critical AI-enabled features, including scorecards, performance thresholds, and proactive alerting for any regressions.
• Establish a standardized conversational taxonomy and develop recurring reporting mechanisms across voice and text interactions to identify key drivers, track trend movements, and highlight emerging issues.
• Drive measurable improvements in at least two key student or operational outcome metrics through the application of data science-led strategies and interventions.
• Develop and maintain a prioritized roadmap of Machine Learning (ML) and analytics initiatives, clearly defining owners, success metrics, and decision timelines, reviewed on a regular cadence.
• Guide the team in building and refining models for next best action, propensity scoring, and proactive interventions, ensuring they are optimized for student success and institutional efficiency.
• Enhance the multimodal intelligence capabilities by integrating signals from various interaction channels to create a holistic understanding of the student journey.
• Champion the use of data science to personalize student experiences, ensuring that interventions and guidance are tailored to individual needs and circumstances.
• Contribute to the ethical development and deployment of AI, ensuring fairness, transparency, and accountability in all data science applications.
• Stay abreast of the latest advancements in AI, ML, NLP, and generative AI, evaluating their potential application to enhance Risepoint's offerings and student outcomes.
• Mentor and develop team members, fostering their professional growth and empowering them to take on challenging projects and leadership opportunities.
• Act as a key technical advisor, providing insights and recommendations on data strategy, ML infrastructure, and analytical best practices.
• Ensure that data privacy and security protocols are rigorously adhered to in all data science activities.
• Drive a data-informed culture across the organization, promoting the use of insights to guide strategic planning and operational improvements.
• Measure and report on the impact of data science initiatives, demonstrating value and informing future investments.
• Collaborate with cross-functional teams to identify new opportunities for leveraging data science to solve business problems and improve the student experience.
• Develop and maintain strong relationships with university partners, understanding their unique challenges and opportunities for data-driven solutions.
• Ensure the scalability and efficiency of data science solutions to support Risepoint's growing user base and program offerings.
• Advocate for best practices in data management, data quality, and MLOps to ensure the reliability and maintainability of production systems.
• Contribute to the overall technical vision and strategy of the company, aligning data science efforts with broader business objectives.