What are the responsibilities and job description for the Scientific Manager position at Excelra?
Job Summary
Excelra is seeking a highly skilled and motivated Scientific Manager I with strong expertise in bioinformatics and omics data analysis to join our Bioinformatics division. The ideal candidate will have a deep understanding of multi-omics integration, computational pipeline development, and statistical modeling, and will play a key role in designing and executing analytical strategies to address complex biological questions.
Key Responsibilities
- Lead and execute projects involving omics data (e.g., scRNA-seq, ATAC-seq, RNA-seq, WGS, ChIP-seq, exome sequencing, genome annotation).
- Build and optimize computational pipelines/packages to support genomics data analysis, biomarker discovery, drug repurposing, patient stratification, disease modeling, and data integration.
- Analyze and integrate omics datasets (genomics, transcriptomics—bulk and single cell, proteomics, etc.).
- Collaborate with cross-functional teams, including PhD-level scientists, to drive innovation in data-driven research and hypothesis generation.
- Present scientific results and hypotheses to both internal and external stakeholders in a clear and actionable manner.
- Write research papers, reports, and summaries, contributing to knowledge generation and scientific communication.
- Stay current with advancements in the field, incorporating new methods and tools as appropriate.
Qualifications Required
- Master’s degree with 3–5 years of industry experience in Bioinformatics, Computational Biology, Computer Science, or a related field.
- Proven track record in omics data analysis (NGS, scRNA-seq, WGS, etc.) and downstream interpretation.
- Deep expertise in programming/scripting using R (including package development, dplyr, Shiny, R Markdown, data simulation), Python, Perl, and Bash.
- Solid understanding of statistical methods and machine learning approaches, with experience in simulations and novel statistical modeling.
- Familiarity with bioinformatics tools, databases, and workflow management systems such as Docker and Nextflow.
- Background in population genomics, including GWAS, eQTL/pQTL analysis, and WES/WGS data.
- Experience with Linux environments, cloud computing platforms (AWS/GCP), and relational databases (Postgres, MySQL, Oracle).
- Skilled in using version control systems such as GitHub.
- Strong communication and collaboration skills with an ability to work effectively in cross-functional teams.
- Scientific curiosity and the ability to generate innovative, data-driven hypotheses.
Salary : $140,000 - $160,000
