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Bioinformatician -Omics Data

Excelra

Scientific Manager (Bioinformatics)

Location

Europe

Work Mode

Hybrid

Who are we?

  • Excelra is a leader in biopharma data and analytics, that uniquely blends scientific understanding with technological expertise. This dual mastery empowers innovative drug discovery and development, transforming research data into actionable insights for groundbreaking discovery.
  • We have locations in Hyderabad (head offices – India), Ghent (Belgium), London (UK), Utrecht (The Netherlands), and Boston/SFO (US).
  • Website:

www.excelra.com

About the role

  • We are hiring a Scientific Manager to turn complex biological questions into scalable, reproducible analytical systems for Life Sciences R&D clients.
  • The role combines hands-on bioinformatics, applied machine learning and scientific software architecture. You will lead projects end to end: scoping with stakeholders, designing data models and pipelines, building algorithms and platforms, and communicating results to pharma and research partners.

Key Responsibilities

Scientific Leadership and Stakeholder Engagement

  • Lead bioinformatics projects for pharma and biotech stakeholders, from problem framing to delivery of results and recommendations.
  • Gather requirements with lab scientists, data engineers and domain experts; define processes, data formats and success criteria.
  • Present analyses and scientific findings clearly to technical and non-technical audiences.
  • Manage projects with Agile methods: roadmaps, backlogs, sprint planning and code reviews.

Omics Analysis and Interpretation

  • Design and run analyses across genomics, exomes, bulk transcriptomics, metagenomics and comparative genomics.
  • Build variant annotation, filtering and interpretation pipelines from VCF inputs, including oligogenic and pathogenic variant combinations.
  • Perform differential expression, concordance and enrichment analyses, and interpret them in a biological context.
  • Support target identification and therapeutic modality work, such as antisense oligonucleotide (ASO) off-target prediction.

Machine Learning and Knowledge Graphs

  • Develop interpretable ML models (supervised and unsupervised) for biological prediction tasks, with attention to imbalanced data and explainability.
  • Build and query knowledge graphs integrating PPI, co-expression, homology, disease, HPO and GO data.
  • Evaluate knowledge graph embeddings and benchmark predictive methods rigorously.

Pipelines, Data Engineering and Platforms

  • Architect reproducible, modular workflows (Snakemake, Targets, Docker) on HPC (Slurm, LSF) and cloud (AWS, Databricks, Seven Bridges).
  • Design relational and graph database schemas for fast retrieval of annotations and results.
  • Build full-stack scientific web applications and dashboards (Django, FastAPI, R Shiny, D3.js).
  • Maintain large codebases following SDLC good practice: testing, CI/CD, version control and code review.
  • Mentor bioinformaticians and contribute to team standards and reusable tooling.

Required Qualifications and Experience

  • A PhD in Bioscience engineering, Bioinformatics, computer science, Computational Biology, Data Science, Computer Science, Genomics, Systems Biology, or a related discipline– or an MSc with 5+ years of equivalent experience. You can demonstrate this through peer-reviewed publications, contributions to public code repositories, or relevant project work.
  • Proven delivery of end-to-end projects: data modelling, algorithm development, pipeline engineering and software architecture.
  • Strong background in genomics and transcriptomics, including variant interpretation and differential expression analysis.
  • Hands-on experience applying machine learning to biological data, with a track record of benchmarking and evaluation.
  • Experience building and maintaining production-grade pipelines on HPC and cloud infrastructure.
  • Experience with functional annotation, ontologies (GO, HPO) and biological network analysis.
  • Solid biostatistics: experimental design, hypothesis testing and correlation analysis on omics and clinical data.
  • Experience working directly with external stakeholders, ideally in pharma or biotech.
  • Excellent written and spoken English; peer-reviewed publications are expected.

Technical Skills

  • Candidates should be strong in most areas below; depth in Python and R is essential.
  • Area

Tools and Methods

Programming

  • Python, R, Bash, SQL; Java and JavaScript a plus
  • Pipelines and Workflows

Snakemake, R Targets, Docker, CI/CD

Databases

  • PostgreSQL, MySQL, Oracle, Neo4j; schema design and query optimisation
  • Machine Learning
  • scikit-learn, caret, PyKEEN, graph-tool; classification, regression, clustering, explainability
  • Bioinformatics Tools

Sequence alignment (bowtie, BWA), DESeq2, edgeR, Cuffdiff, VCF processing, nanopore metagenomics

What Do We Offer?

  • A challenging job environment with advancement opportunities.
  • Flexible hybrid working in an international setting.
  • A dynamic company with an open culture, easy communication, and an ambitious vision.
  • A rich and global team with a mix of backgrounds, experiences, and expertise.
  • Independence and flexibility.
  • Opportunities to work across diverse research programs, leading bioinformatics projects and design and develop models with mentoring opportunities.
  • An attractive salary package with extra-legal benefits.

What Success Looks Like in the First Year

  • Leads at least two client or internal projects to delivery with documented, reproducible outputs.
  • Establishes or improves a shared pipeline or platform component used by the wider team.
  • Becomes a trusted scientific point of contact for key pharma or biotech stakeholders.