• Lead and shape Unobravo’s data science and machine learning strategy, driving measurable improvements in therapeutic and commercial outcomes such as patient conversion, retention, and patient–therapist matching. • Own the ML/DS roadmap across multiple business functions, prioritising high-impact initiatives and ensuring models deliver long-term, compounding value rather than isolated experiments. • Build and maintain responsible AI standards, including model governance, explainability, fairness, GDPR compliance, observability, drift detection, and bias mitigation across markets and patient groups. • Partner closely with clinical, product, marketing, commercial, and data engineering teams to translate business and therapeutic challenges into scalable ML solutions and actionable insights.

• Drive insight generation for complex projects both independently and in collaboration with cross-functional teams. • Develop models of cost and quality in support of our navigation and match services • Identify opportunities to better engage and navigate members so that we can drive top quartile outcomes at bottom quartile costs. • Develop a deep understanding of how our products are being used and identify opportunities to better serve our members’ needs. • Prototype novel approaches to measuring or inferring product and business performance. • Scale our impact so we can bring our services to more people in need.

• Desarrollo y creación de modelos de inteligencia artificial. • Análisis de datos y evaluaciones. • Diseño y montaje de sistemas de monitorización de modelos de inteligencia artificial. • Colaboración en un equipo dinámico y responsable.

- Help support Auto and Home Actuarial team update Base Rate Offset tool into Python. This role requires strong Python skills as well as self-learning skills. - Contributes to the development and implementation of predictive analytics through the application of adva nced statistical and analytical techniques in order to deliver data driven insights supporting business objectives. - Uses appropriate modeling techniques to address business needs. - Utilizes broad knowledge of advanced modeling techniques and procedures to develop new modeling techniques and skills. Conducts appropriate evaluation of model performance. - Designs and publishes reports to communicate results and track model performance. - Develops various programs including predictor and response variable programs. Reviews programs to ensure they conform to quality standards. - Supports preparation of internal/external, structured/unstructured data sets to build/rebuild/refresh predictive models. - Creates ad-hoc data analyses, as needed Communicates analytics to other modelers as well as to non-technical business partners. - Contributes to the continuous improvement of the modeling process. Contributes to the continuous improvement of the modeling process.