Bioinformatics Scientist

Celcuity•Plymouth, MN

3d•$110,000 - $120,000

About The Position

The Bioinformatics Scientist will focus on complex experimental and clinical bioinformatics data sets. This role requires a strong background in tissue-based animal model assays, cell-based assays, cell pathway signaling, and biochemistry, particularly as it relates to biologically dysfunctional systems. The scientist will be involved in the design and execution of various -Omics experiments, including bulk, single-cell, and spatial transcriptomics, WES, epigenomics, metabolomics, and proteomics. Demonstrable hands-on experience with experimental sample-to-data workflows for one or more platforms is essential. The role involves executing analysis pipelines using R and/or Python, with a focus on implementing bioinformatics practices for reproducible and modular analysis, such as markdown documentation, r/v env locks, and git. Proficiency in data science skills, including exploratory data analysis, wrangling (discovery, structuring/transformation, cleaning, enriching/reduction, validating, and publishing), and visualization using R and/or Python, is required. The scientist will be responsible for writing and improving existing code in R and Python for exploratory and validation data analysis of large-scale multi-omics (DNA, RNA, protein) datasets. Experience with processing and organizing large datasets from public repositories using structured queries and wrangling data for compatibility with analytical pipelines in a cloud-based computing environment is also a key aspect of this position. Attention to documentation and standards for reproducibility of code and data integrity is paramount.

Requirements

A Ph.D or equivalent experience in biological or biochemical sciences with strong skills in one or more Omics approaches (transcriptomics, genomics, proteomics)
Experience in Data Science, Bioinformatics or related computational disciplines.
Experience in working with large omics datasets using R/Python.
Strong understanding of cell biology especially with respect to basic biochemistry, cell signaling, cell replication, transcription, translation processes.

Responsibilities

Strong background in tissue-based animal model assays, cell-based assays, cell pathway signaling, biochemistry especially as related to biologically dysfunctional systems.
Strong background in design and execution of -Omics experiments (bulk, single-cell, spatial transcriptomics, WES, epigenomics, metabolomics, proteomics, etc), demonstrable hands-on experience with experimental sample-to-data workflows for one or more platforms.
Experience executing analysis pipelines using R and/or Python with attention to implementing bioinformatics practices for reproducible and modular analysis (markdown documentation, r/v env locks, git).
Proficiency in data science skills related to exploratory data analysis, wrangling (knowledge of coding and processes related to key steps - discovery, structuring/transformation, cleaning, enriching/reduction, validating, and publishing), and visualization using R and/or Python.
Writing and improving existing code in R and Python for exploratory and validation data analysis of large-scale multi-omics (DNA, RNA, protein) datasets.
Experience with processing and organizing large datasets from public repositories using structured queries and wrangling data to be compatible with analytical pipelines in a cloud-based computing environment.
Attention to documentation and standards for reproducibility of code and data integrity.