- Company Name
- ARCA
- Job Title
- Genomics Data Scientist
- Job Description
-
**Job Title**
Genomics Data Scientist
**Role Summary**
Analyze and interpret large-scale genomic datasets (WGS/WES, RNA‑Seq, variant calls) to generate actionable insights for research, clinical decision‑making, and population health. Develop, maintain, and optimize bioinformatics workflows and pipelines, applying advanced statistical modeling and computational genomics techniques. Collaborate with multidisciplinary teams across science, data, and clinical domains.
**Expectations**
- Deliver robust, reproducible analyses and models that inform research and clinical outcomes.
- Produce clear, well‑documented code and reports.
- Contribute to continuous improvement of data pipelines and analytical methodologies.
- Communicate findings effectively to both technical and non‑technical stakeholders.
**Key Responsibilities**
- Process and analyze high‑throughput genomic sequencing data (WGS, WES, RNA‑Seq).
- Develop and maintain bioinformatics workflows (e.g., alignment, variant calling, QC).
- Apply statistical modelling to integrate genomic and clinical information.
- Generate biological insights supporting research projects and population‑health initiatives.
- Collaborate with bioinformaticians, biostatisticians, clinicians, and data scientists.
- Document code, analytical procedures, and results thoroughly.
- Keep abreast of emerging tools, methodologies, and best practices in genomics and biostatistics.
**Required Skills**
- Proficiency in R and/or Python for data analysis and workflow scripting.
- Hands‑on experience with genomic data formats and tools (e.g., BAM/VCF, GATK, STAR, SAMtools).
- Strong understanding of statistical methods for biological data (regression, mixed models, multiple testing, survival analysis).
- Ability to design, implement, and troubleshoot computational pipelines.
- Excellent written and verbal communication; clear documentation.
- Team‑player mindset; effective collaboration across domains.
- Familiarity with TRE/SDE/HPC environments is advantageous.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Bioinformatics, Biostatistics, Computational Genomics, Data Science, or closely related field.
- Demonstrated experience or coursework in genomic data analysis and statistical modeling.
- No mandatory professional certifications required, but relevant credentials (e.g., Certified Genomics Professional) may be considered a plus.