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Uxue Dobao
Data Scientist en AQuAS
Professional Background
Uxue Lazcano Dobao is a dedicated and accomplished Data Scientist with a robust background in bioinformatics and molecular biology. Currently, Uxue is making significant contributions to the field as a Data Scientist at AQuAS, where she applies her expertise in data science and big data to propel insights in healthcare and public health initiatives. With her extensive experience in various high-profile organizations, Uxue has honed her skills in handling complex data environments and developing innovative approaches to data analysis.
Before her current role, Uxue was a Data Scientist at Heuristik, where she collaborated with cross-functional teams to solve intricate data-related challenges. Additionally, her leadership and mentoring capabilities were showcased during her tenure as the Barcelona City Lead at Saturdays.AI, a community that fosters the development of artificial intelligence skills among aspiring data professionals. Uxue has also contributed to the academic and research community as a PhD student at the Instituto Hospital del Mar de Investigaciones Médicas (IMIM), where she engaged in cutting-edge research that intersected both data science and healthcare.
With a strong foundation in bioinformatics, Uxue's career trajectory has taken her from roles as a Bioinformatician at Instituto Hospital del Mar and CIC bioGUNE to her significant positions as a Data Scientist. Throughout her career, she has been driven by a commitment to leveraging data to enhance the understanding of biological systems and improve public health outcomes.
Education and Achievements
Uxue's educational background is impressive, with advanced degrees focused on the intersection of data science, bioinformatics, and molecular biology. She completed her Master's degree in Bioinformatics at the prestigious Universitat Autònoma de Barcelona, where she gained critical insights into computational biology and data analysis techniques. This program equipped her with a blend of knowledge that bridges the biological sciences and advanced data methodologies.
Further building on her expertise, Uxue pursued postgraduate studies in Data Science and Big Data at the renowned Universitat de Barcelona. This additional academic training provided her with the analytical and technical skills necessary to excel in a rapidly changing field, ensuring she remains at the forefront of data-driven approaches in health-related research and applications. Her fundamental undergraduate degree in Bioquímica y biología molecular from Universidad del País Vasco (Euskal Herriko Unibertsitatea) laid the groundwork, giving her a solid understanding of biochemical processes and molecular biology.
Notable Achievements
Over her career, Uxue's work has not only contributed to the organizations she has been part of but has also significantly influenced the domains of data science and bioinformatics. Her ability to analyze large datasets and extract meaningful insights has made a palpable impact on the organizations where she has worked. At AQuAS, she has been instrumental in driving data-driven strategies that inform health policies and improve patient outcomes.
Her role as Barcelona City Lead for Saturdays.AI demonstrated Uxue's commitment to community engagement and education, helping to nurture the next generation of data scientists and AI professionals. Uxue has also played a crucial role as a mentor in helping others navigate their careers in data science, particularly those interested in entering the fields of artificial intelligence and analytics.
Uxue's research initiatives as a PhD student at IMIM reflect her dedication to advancing scientific knowledge through rigorous data analysis. She has been actively involved in projects that combine her passions for data science and health, striving to utilize data in ways that foster innovation in the healthcare sector. The experience she amassed from various prestigious institutions has positioned her as a competent figure in the realms of bioinformatics and data science.
Achievements
