Skills

Technical skills

• Bioinformatics: Bulk & single-cell omics (RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation); cancer genomics; immune repertoire/VDJ analysis (MiXCR); QC, normalization, differential analysis, clustering/annotation; reproducible analysis and reporting.
• Programming: Python (data analysis, pipelines, visualization, Streamlit); R (statistics, scRNA-seq ecosystem); SQL (querying, basic modeling); bash/Linux; Git.
• Data Engineering: ETL/ELT pipeline design; ingestion & normalization of semi-structured CSVs; workflow orchestration with Airflow; GCS → BigQuery data loads; data modelling (star schema / dimensional modelling); dbt-style testing (schema + data quality checks); Docker/Compose; CI/CD basics (GitHub Actions); logging & validation.
• Other: Machine learning for genomics (foundations and prototyping); documentation best practices; familiarity with clinical data standards (CDISC: SDTM/ADaM) and SAS (basic).

Soft Skills

• Teamwork
• Leadership (technical mentoring and task coordination)
• Scientific communication (translating complex analyses to non-technical stakeholders)
• Critical thinking & rigor (experimental design mindset, interpretation, troubleshooting)