IPREMOM is a FemTech company created to translate our scientific knowledge into molecular tests developed for the early diagnosis of gestational diseases such as preeclampsia.
Our main activity is to provide innovative solutions that protect women and their children from pregnancy-related complications. We want to create a world where pregnant women do not fear for their health.
IPREMOM's scientists are experts in obstetrics, biotechnology, and computational biology with a passion for improving maternal and fetal health.
We are seeking a Computational Biologist to lead the data analysis tasks developed by iPremom, as Data Science Lead, forming part of the computational biology research team at the Carlos Simon Foundation. The candidate will focus on extracting meaningful information from extensive RNA sequencing data from human subjects, implementing predictive models from RNA sequencing data, and creating a platform of pipelines to support them. The candidate will collaborate with scientists, other professionals, and collaborators from various national and international institutions to translate the results into novel applications.
Requirements: Master's degree in statistics, mathematics, computer science, bioinformatics, biostatistics, or another related field Five or more years of experience (Ph.D. is a plus) manipulating data sets and building statistical models in bioinformatics or any computational/quantitative biology field. Broad experience in designing and building scalable data pipelines to reach data-driven scientific conclusions. Proficiency in statistical computer languages (Python, R) and scripting in Linux, Bash, and high-performance computing resources Knowledge of resource management with SLURM Knowledge of RNA sequencing-based transcriptomics analysis (e.g., normalization methods, differentially expressed genes, and feature selection for machine learning methods) Knowledge of a variety of machine learning techniques (e.g., clustering, decision tree learning, and artificial neural networks) and their real-world advantages/drawbacks Knowledge of advanced statistical techniques and concepts (e.g., regression, properties of distributions, and statistical testing) and experience with applications Version and project management with GitHub Experience in organizing results in reports or notebooks (e.g., Rmarkdown, Quarto, or Jupyter) Ability to organize workloads and manage competing priorities. Resolve, dynamism, and strong problem-solving skills. Desirable skills: Management, leadership, and team supervision Knowledge of pregnancy complications and other somatic conditions Knowledge of modern biological data warehouses (SRA, GEO) Experience with cloud computing platforms (AWS preferred) Additional skills: Drive to learn and master innovative technologies and techniques from next-generation sequencing applications. Experience visualizing/presenting data to collaborators. Excellent written/verbal communication skills for coordinating across teams. Professional level ability in Spanish and English Fast learner Responsibilities: Lead and manage a team of data scientists, data engineers, and other professionals involved in data analysis. Oversee the entire lifecycle of data science projects, from problem identification to solution implementation and impact assessment. Efficiently manage team resources, including human resources, time, and budget allocated to data science projects. Provide technical guidance and advice to team members in problem-solving and technical decision-making. Maintenance, management, and analysis of proprietary and public RNA sequencing datasets from human subjects in the diagnostic area of women's and reproductive health RNA sequencing analysis from liquid biopsies as a non-invasive early diagnosis tool Use predictive modeling to reach sound biological results. Develop custom data models and algorithms to apply to datasets. Implement innovative approaches and develop working tools and techniques to address objective biological questions. Drive optimization and improvement of model development Analyze and monitor model performance and data accuracy. Automate workflows and manage pipelines and scripts. Assess the effectiveness and accuracy of data sources and data-gathering techniques. Establish and maintain standards and best practices for data analysis within the team, ensuring consistency and quality of work. Collaborate with scientists to prioritize tasks for follow-up, testing, and/or validation of hypotheses. Collaborate with business leaders to understand strategic objectives and define the direction of data science projects. Work closely with other departments (e.g., experimental lab, marketing, or regulatory) to understand their needs and provide data-driven solutions. Contribute to publications in peer-reviewed journals resulting from research aims and methodological innovations. Keep up to date with trends and advances in data science, promoting innovation and the application of innovative technologies and approaches. Salary: The salary range for this position will depend on the suitability of the candidate for the requested profile. Full-time employment contract What do we offer? Participate in a research project framed within women's health in a highly motivating team! Opportunities for professional/personal growth and the application of knowledge by collaborating with colleagues from the same professional field. Workplace: Our lab facilities are in the "Parque Tecnológico de Paterna," Paterna (Valencia, Spain) Application Process: In case of interest, send your application to the following email address: ******
#J-18808-Ljbffr
