- Data Management and Pipelines: Develop and maintain efficient data management processes, including data collection, storage, cleaning, integration, and automated data pipelines for diverse datasets related to travel health.
- Workflow Optimization: Streamline data analysis workflows to ensure the efficient and timely delivery of insights and recommendations.
- Data Analysis: Analyze healthcare data using advanced statistical techniques and AI algorithms to develop predictive models and recommendations for travelers' health and safety.
- Data Visualization: Create compelling visualizations and reports to communicate findings and insights to stakeholders, including travelers, healthcare providers, and decision-makers.
- Research Collaboration: Collaborate with a multidisciplinary team of data scientists, healthcare professionals, and engineers to design studies, conduct research, and develop data-driven solutions.
- Quality Control: Ensure data accuracy and maintain rigorous quality control measures to uphold the integrity of healthcare data.
- Data Interpretation: Interpret statistical results and provide actionable recommendations to enhance traveler health outcomes.
- Documentation: Maintain detailed documentation of data management processes, analysis methodologies, results, and data sources.
- Continuous Learning: Stay updated with the latest developments in biostatistics, AI, data management, and travel health to drive innovation.
- Master's or Ph.D. in Biostatistics, Statistics, Data Science, or a related field.
- Proficiency in statistical software such as R, SAS, or Python.
- Strong analytical and problem-solving skills.
- Proven experience in data management, ETL processes, and workflow optimization.
- Experience in healthcare data analysis, epidemiology, or related fields.
- Excellent communication skills to convey complex data findings effectively.
- Commitment to data quality and attention to detail.
- Ability to work both independently and collaboratively in a dynamic startup environment.
- Knowledge of AI and machine learning techniques is a plus.
- Master's or Ph.D. in Biostatistics, Statistics, Data Science, or a related field.
- Proficiency in statistical software such as R, SAS, or Python.
- Strong analytical and problem-solving skills.
- Proven experience in data management, ETL processes, and workflow optimization.
- Experience in healthcare data analysis, epidemiology, or related fields.
- Excellent communication skills to convey complex data findings effectively.
- Commitment to data quality and attention to detail.
- Ability to work both independently and collaboratively in a dynamic startup environment.
- Knowledge of AI and machine learning techniques is a plus.
- Duration: 6 months (renewable)
- Starting date: October
- Contract: (part or full time) Full time
- Salary Range: Technician II-A
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Data Analyst and Biostatistician for Traveller's health - Barcelona, España - Instituto de Salud Global de Barcelona
Descripción
What We Are Looking for
About Us : Famba is an innovative project on a mission to enhance the health and well-being of international travelers across the globe. We harness the power of AI, data analytics, and biostatistics to create cutting-edge solutions for the travel health industry. We are seeking a talented Data Analyst and Biostatistician to join our team and play a crucial role in our journey to revolutionize traveler's health.
Position Overview : As a Data Analyst and Biostatistician at Famba, you will be at the forefront of improving the health of travelers worldwide through data-driven insights and innovative solutions. This role offers you the opportunity to combine your expertise in data analysis and biostatistics with a strong focus on data management, including data pipelines, to address the unique challenges faced by travelers and shape the future of travel health.
This is a collaboration between Hospital Clínic Department of International Health and the Biomedical Data Science Group at ISGLOBAL. As such, the candidate will be exposed to multidisciplinary research team of clinicians and data scientists.
Key Responsibilities
Qualifications
Conditions
Conditions