About the role
<div class="content-intro"><p><strong>Conviva is the first and best place to understand and optimize digital customer experiences. Our Operational Data Platform harnesses full-census, comprehensive client-side telemetry—capturing every aspect of customer experience and engagement across all devices and linking them to the performance of underlying services, in real-time and at a fraction of the cost of alternative solutions. Conviva computes quality of experience across all users and all devices, in real time. We combine user actions with app and system responses to give your technology, business, and operations teams AI-powered insights into any issues impacting user experience and engagement. Trusted by industry leaders like Disney, NBC, and the NFL, Conviva revolutionizes how businesses understand customer experience and engagement, maximizing satisfaction, conversion, and revenue.&nbsp;</strong></p></div><p>We are looking for a <strong>Senior Data Scientist with a strong foundation in Machine Learning, Algorithms</strong>, and experienced with AI-native development to help drive our AI Initiatives and contribute to the development of our Real-Time Analytics Platform. This is a hands-on, technically deep role ideal for individuals with a background in Computer Science or Statistics who are passionate about building scalable, intelligent systems — and who actively leverage AI tools to accelerate their work.&nbsp;</p> <p>&nbsp;</p> <p><strong>What Success Will Look Like:</strong>&nbsp;</p> <ul> <li>Design, build, and optimize ML models and solutions — spanning <strong>traditional statistical ML, neural networks, and deep learning</strong> — to solve real-world problems in large-scale, real-time digital performance analytics.</li> <li>Develop innovative approaches for <strong>predictive modeling, anomaly detection, and automated alerting</strong> using time series and other complex datasets.</li> <li>Apply the <strong>full algorithm spectrum</strong>: from classical methods (regression, tree-based ensembles, clustering) to advanced deep learning architectures (transformers, LSTMs, CNNs) as the problem demands.</li> <li>Support AI initiatives including designing AI-driven alerts and contributing to AI roadmaps.</li> <li>Develop POC code and implement ML solutions that improve product capabilities — using <strong>AI coding tools (e.g., Claude, Cursor) natively</strong> to accelerate prototyping, code review, and iteration cycles.</li> <li>Process and analyze large-scale data using <strong>Ray and Spark</strong>.</li> <li>Collaborate with cross-functional engineering and product teams to integrate models into production systems.</li> <li>Stay current with industry trends in AI