The candidate will lead and manage the Data Analysis area of the Carlos Simón Foundation, designing and implementing controlled and highly specialized genomic analysis procedures, developing novel analytical methods, and driving the strategy for the generation, management, and utilization of genomic data for the Foundation.
Key Accountabilities and Responsibilities
Lead and manage a team of data scientists, providing guidance, mentoring, and fostering a collaborative work environment with continuous learning.
- Design data analysis pipelines following the most reliable methodologies in the field, including analysis checkpoints, data annotation, and documentation of processes and results.
- Collaborate with Principal Investigators (PIs) of the Institution in designing genomic experiments to ensure subsequent analysis aligns with study objectives.
- Design a workflow model between the data scientist team and analysis projects, establishing task allocation, deadline management, and responsibilities.
- Play a cross-functional role, providing assistance to various ongoing projects, focusing on leading the development and maintenance of bioinformatics analysis pipelines and genomic, metagenomic, and transcriptomic databases.
- Manage the team of IT scientist responsible for performing bioinformatics analysis of raw sequencing data and developing/maintaining databases necessary for comparisons, statistics, and knowledge generation, Big Data, and IoT.
- Establish deadlines for ongoing projects and allocate resources to achieve established objectives and deadlines.
- Prepare reporting to inform on the progress of ongoing projects and results, interacting with both PIs and the Presidency.
- Supervise the proper execution of tasks by team members to identify potential issues before project analysis tasks are completed.
- Establish indicators and double-check procedures to guarantee analysis results.
- Participate in developing quality control lines, processing, and analyzing multi-level biological data (e.g., RNA-seq, GWAS, proteomics, epigenomics, metagenomics, single-cell RNA-seq).
- Implement procedures to ensure shared knowledge management (proper knowledge transfer, technical documentation of projects, procedures, etc.).
- Collaborate with team members, experts, internal and external projects to propose, develop, and evaluate innovative machine learning models for understanding data, its application, effectiveness, and safety.
- Establish work procedures to identify, quantify, and obtain tangible improvement proposals regarding data analysis.
- Implement a technological surveillance system to incorporate the most novel and potentially impactful analytical methodologies into work pipelines.
- Propose and oversee research projects in data analysis aligned with the Foundation's genomic studies that can add value to the data.
Required skills and experience
- Bachelor's degree or engineering degree in any scientific-technical discipline (biology, biotechnology, chemistry, pharmacy, computer science, mathematics, statistics, or engineering).
- Official Master's Degree in Bioinformatics, Data Science, Biostatistics, or related fields.
- Having completed a doctorate in data science, machine learning, artificial intelligence, or related fields is positively valued.
- Minimum of 8 years of experience performing the described functions.
Other requirements:
- Fluent spoken and written English enabling the writing of scientific papers and presenting results at scientific conferences.
- Sufficient knowledge and proven experience to build and execute analysis pipelines in the fields of genomics and metagenomics.
- Proficiency in programming languages such as Python, R, or related ones, and knowledge of the Linux/Unix environment.
- Comprehensive mastery of computational tools and technologies in molecular biology and massive sequencing.
- Knowledge and proven experience in system administration, database development and maintenance, as well as experience in NGS whole genome data and particularly in working with scRNA-seq/scATAC-seq from FASTQ to analyzed data, both with 10X, SS2, and other formats.
- Understanding of the statistical foundations of analytical methodologies used in genomics.
- Knowledge and proven experience in good software development practices and collaboration tools, including GitHub-based version control, Python package management, and code reviews.
- Ability to explain complex machine learning algorithms and statistical methods to non-technical stakeholders.
- Extensive experience in high-performance computing.
- Experience in programming in Java, Ruby, PostgreSQL, or Bash will be appreciated.
- Ability to quickly understand scientific, technical, and process challenges and break down complex problems into actionable steps.
- Ability to work in a frequently changing environment and interpret management information to modify plans.
- Ability to establish priorities, manage workload, and complete agreed-upon activities always on time.
- Excellent communication skills. Ability to network, influence, and build relationships. Demonstrated ability to interact effectively and work productively in an interdisciplinary team.
- Ability to manage a team, handle projects, establish deliverables, identify contingencies, and meet deadlines.
- Strategic thinking: ability to see the "big picture".
- Capable of proposing innovative ideas
We offer:
- Full package with attractive salary conditions based on the candidate's skills, experience, and suitability once selected.
- Hybrid work mode.
- Future working trajectory within the Foundation
Application Process:
If you are interested, we would appreciate it if you could send us your application to the following email address: iserra@fundacioncarlossimon.com
About CARLOS SIMÓN FOUNDATION FOR RESEARCH IN WOMEN’S HEALTH
Carlos Simón Foundation for Research in Women's Health is a non-profit organization located in Valencia ( Spain) founded and directed by Professor Carlos Simón, professor at the University of Valencia and renowned clinical researcher in the field of obstetrics and gynecology.
We are a multidisciplinary team made up of more than 40 professionals. We work to create a world in which women's health pathologies that affect the uterus are no longer a barrier to their quality of life and reproductive desire. Our main activity is biomedical research in the field of reproductive medicine and women's health, and the development of initiatives aimed at improving our knowledge in the field and its clinical application.