Senior Scientific Data Scientist

Arctoris is seeking a Senior Scientific Data Scientist / Pipeline Engineer to design, implement, and maintain the analytical pipelines that power our data-driven drug discovery platform.

This role is ideal for a scientist-turned-coder or data scientist with strong Python skills, statistical modelling expertise, and experience with bioassay data - paired with solid software engineering discipline.

If you thrive at the intersection of biology, data, and scientific automation, enjoy partnering with wet-lab teams, and want to build robust tools that accelerate therapeutic discovery, this is the ideal opportunity.

Main Responsibilties Scientific Analysis & Pipeline Development

Build, maintain, and extend Python-based analytical pipelines for diverse bioassay datasets (biochemical, biophysics, and cell-based assays).

• Implement robust statistical and modelling workflows, including:
• dose-response modelling and curve fitting (e.g., 4PL, mechanistic models)
• QC and normalisation frameworks
• plate-level statistics and data validation
• Translate scientist workflows into reproducible, automated analysis pipelines.

Data Engineering & Workflow Structuring

Design structured ETL/ELT processes for experimental data ingestion, curation, and transformation.

Develop clean, maintainable, well-tested Python codebases using solid software engineering principles.

Use lightweight workflow tools (e.g., Snakemake, Luigi, or similar) to organise multi-step scientific analyses.

Scientific Collaboration & Communication

Partner closely with wet-lab scientists to:

• understand assay logic and experimental design
• identify improvements to data structures and analysis readiness
• streamline file preparation and data handover
• Provide input on experimental interpretation where it helps clarify analytical or QC decisions.

Infrastructure & Tooling (Nice-to-Have)

• Support backend integration with cloud storage or databases (AWS S3, PostgreSQL, etc.).
• Contribute to internal scientific tooling, dashboards, or lightweight GUIs (optional).
• Assist with continuing evolution of scientific data architecture.

Qualifications and Experience Scientific & Analytical

• Strong experience analysing plate-based bioassay data (384- or 1536-well formats).
• Proficiency in Python for scientific computing, including NumPy, Pandas, SciPy, curve fitting libraries such as lmfit, and visualisation libraries such as Matplotlib/Seaborn. Experience with scikit-learn for exploratory analysis (e.g., PCA, clustering), data validation tools (e.g., Pandera), and scientific libraries such as Biopython or RDKit is highly beneficial.
• Solid understanding of statistical modelling, curve fitting, and QC in experimental biology.
• Ability to work across multiple scientific domains and adapt to varied assay formats.

Software Engineering

• Modular design and code organisation
• Testing (PyTest/Unittest)
• Version control (Git)
• Clear documentation and reproducibility
• Experience developing end-to-end data or analysis pipelines.
• Able to work fluidly across scientific teams and translate scientific needs into computational workflows.
• Clear and structured communicator; capable of articulating analytical choices and modelling approaches.
• Strong problem-solving mindset.
• Experience with lightweight workflow managers (e.g., Snakemake, Luigi).
• Familiarity with AWS or cloud storage systems.
• Database experience (PostgreSQL/MySQL) and data modelling.
• Background in biophysics, cell biology, enzymology, or other relevant scientific domains.
• Exposure to containerisation (Docker) or CI/CD (GitHub Actions).
• Ability to develop simple user-facing interfaces (e.g., Streamlit).

About us

Arctoris is a tech-enabled biopharma platform company founded and headquartered in Oxford, UK with its US operations based in Boston and its Asia-Pacific operations based in Singapore. Arctoris combines robotics and data science with a world-class team for small molecule and biologics discovery.