• Extract data to build metrics or create/update Tableau dashboards to track success toward company, department, and customer KPIs • Share insights with internal and external customers regarding drivers of success or areas of opportunity • Analyze data in new areas to help prioritize areas of focus • Consult with internal and external customers to develop new dashboards, metrics, KPIs, outcomes evaluation, or ROI • Respond to ad hoc analytic requests from internal and external customers • Understand and use the data warehouse and relational databases • Ensure accurate quality of deliverables by participating in peer review

• Timely delivery of accurate quantitative data and insights • People management for a team of roughly seven data scientists • Mentoring team members on critical thinking and technical skillset • Partnering with Data Engineering teams to build and maintain data products • Continuous development of experimentation and measurement best practices

• Query and analyze large complex datasets • Use data mining, statistics, and machine learning to discover insights • Build predictive models and propose actionable solutions • Support drug discovery and biotherapeutics efforts • Perform quantitative modeling of complex chemical and biological systems • Collaborate with administrative leaders, clinicians and IT specialists • Build machine learning models • Design and implementation of pilots for validation and optimization

• Diseñar, entrenar y desplegar modelos de Machine Learning y Deep Learning. • Trabajar con grandes volúmenes de datos estructurados y no estructurados. • Implementar soluciones en AWS utilizando SageMaker. • Optimizar pipelines de datos y procesos de entrenamiento. • Versionar código y modelos con Bitbucket. • Documentar resultados y presentar insights a stakeholders técnicos y de negocio.