Sr. Research Scientist - Bioinformatics Cancer Biology - Research Data Science
Yoh Life Sciences is seeking a Sr. Research Scientist;
this is a direct hire opportunity with our San Francisco client. The candidate will be responsible will have the opportunity to work in a fast-paced and highly collaborative environment and impact high-level decision making on internal pipeline and external collaboration. The scientist will be responsible for developing and employing rigorous statistical modeling and bioinformatics methods, interpreting and integrating large scale datasets to enable research objectives. The successful candidate will have the ability to formulate scientific questions into coherent analytical efforts and communicate analysis results and scientific findings to project teams and across different research functions.Essential Functions:
Knowledge, Experience and Skills:
- Develop and implement quality assessment, statistical analysis and data visualization for multi-omics datasets (e.g., RNA-Seq, single cell sequencing, WES, WGS, Chip-Seq, NanoString, multiplex qPCR, TCR-Seq, BCR-Seq).
- Develop and apply statistical and computational tools for analysis of large omics and high dimensional data from publicly available, commercial, and real-world datasets to enable novel target identification, target assessment, drug combinations, and patient stratification, etc.
- Design and apply bioinformatics algorithms, unsupervised and supervised methods, univariate and multivariate regression analyses to enable the discovery and evaluation of preclinical predictive and prognostic biomarkers for oncology projects.
- Collaborate with cross-functional teams to analyze and interpret complex large datasets and efficiently communicate findings to non-computational scientists and senior leaders.
- Extensive expertise in analyzing, interpreting, and integrating large-scale genomics, transcriptomics, epigenetics, GWAS, proteomics, and high throughput screening data sets.
- Hands on experience in analyzing public omics data sets (e.g., TCGA, GTEx, CCLE, Blueprint, GEO, SRA) is required.
- Expertise in developing algorithms and applications for predictive modeling, pattern recognition, data mining and visualization of large scale multi-dimensional omics datasets.
- Strong statistics knowledge, such as probability theory, univariate and multi-variate analysis, unsupervised and supervised analysis, regression analysis, survival analysis, and feature selection.
- In-depth knowledge of bioinformatics algorithms and their applications in high-throughput experimental techniques, such as Illumina NGS, 10x Genomics, Visium spatial transcriptomics.
- Demonstrated ability to collaborate with research scientists and cross-functional teams, and to manage multiple projects in a fast-paced working environment.
- Demonstrated the ability to synthesize scientific questions into a coherent research effort and communicate scientific findings across different functional teams.
- A proactive and self-motivated individual with a strong work ethic and scientific rigor, ability to work in a dynamic environment and manage multiple objectives in parallel and adapt to changing priorities.
- Excellent oral and written communication skills.
- A PhD in bioinformatics, computational biology, biostatistics, cancer genomics, or a related field with a minimum of 5 years of relevant work experience. Industry experience is preferred.
- Excellent interpersonal and communication skills that foster collaboration and teamwork.
- Excellent problem-solving skills in complex situations.
- Basic understanding of cancer biology, molecular and cell biology.
- Proficiency in R, Python, Perl, JAVA, or C programming languages.
- Proficiency in working in a Linux environment, experience with shell scripting and standard command line tools.