Key Responsibilities

1. Develop and maintain production-grade pipelines for sequence processing, feature extraction, and model-ready datasets.
2. Curate and integrate heterogeneous datasets with strong data hygiene, versioning, and traceability.
3. 3. Partner with external collaborators to define pilot benchmarks, analyze results, and iterate construct designs.
4. Contribute to the algorithmic compute stack alongside engineering (APIs, batch jobs, cloud inference); ensure scalability, robustness, and reproducibility.
5. Track literature and tools in gene expression, codon optimization, mRNA folding, translation initiation, and secretion biology; bring state-of-the-art ideas into production.

Qualifications

1. MSc or PhD in Bioinformatics, Computational Biology, Biostatistics, or related field.
2. 8+ years of industry experience building and shipping bioinformatics pipelines or models tied to experimental outcomes (biologics, synbio, or adjacent).
3. Strong Python (data/ML stack) and statistics; experience turning research code into maintainable, tested components.
4. Expertise with sequence analysis for recombinant expression and NGS processing.
5. Data engineering fundamentals: relational/NoSQL stores, schema design for scientific data, and reproducible data lakes.
6. Clear scientific communication; ability to collaborate with software engineers and external wet-lab teams.