Role Description Analyze and interpret large datasets to identify trends and insights that support business decisions. - Build and validate time series forecasting and statistical models to improve business planning accuracy. - Develop data pipelines and analytical workflows from data collection to visualization using SQL, Python, and cloud-based tools. - Collaborate with cross-functional teams to translate business requirements into data-driven solutions. - Support automation and optimization initiatives by applying machine learning and advanced analytics techniques. - Present analytical findings and model results to stakeholders in a clear and actionable manner. - May telecommute. Qualifications - Master’s degree in Computer Science, Data Science, Statistics, Operations Research, Information Systems or related field. - 2 years of experience in the job offered or related occupation. Requirements - Statistical methods, data modeling, and time series forecasting. - Python and SQL for data extraction and analysis. - Data visualization and reporting tools: Power BI, Tableau, or Excel. - Data processing and automation techniques. - Data Platforms & Warehouses: SQL Server, MySQL, Oracle, or Snowflake. Benefits - Choice of medical, dental, and vision plans in all locations. - Benefit programs that help protect your income if unable to work due to illness or injury. - Paid family leave. - Robust paid time-off program and paid holidays.

• 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.