Data Scientist/Automation

Job Description:

In this role, you will develop and support digital solutions that enable scientists across Receptor Biology Discovery

(RBD) to access, analyze, visualize, and interpret experimental data. You will work closely with scientists, assay developers, and data scientists to build software tools, automated workflows, and data infrastructure that support ,both day-to-day research activities and longer-term digitalization initiatives.

Your work will span scientific software development, data engineering, workflow automation, and scientific data management.

You will help transform laboratory data into accessible, reliable, and reusable digital assets that

accelerate scientific discovery and enable future AI-driven research approaches.

Your Key Responsibilities

• Develop and maintain software applications, dashboards, and visualization tools supporting scientific research.
• Build and support automated workflows for experimental data processing, analysis, and reporting.
• Develop data pipelines that connect laboratory systems, databases, and scientific applications.
• Collaborate with scientists to understand research needs and translate them into practical digital

solutions.

• Improve scientific data quality, accessibility, and traceability through development of standardized

workflows and tools.

• Support assay-specific analysis platforms and scientific data management systems.
• Participate in implementation of new digital capabilities and continuous improvement of existing

platforms.

• Contribute to documentation, testing, and long-term sustainability of scientific software solutions.

Required Experience

• BS + 4 years, MSc + 2 years, or PhD in Data Science, Computer Science, Bioinformatics, Computational

Biology, Engineering, Chemistry, Biology, or a related discipline.

• Experience developing software tools, applications, or automated workflows.
• Experience and proficiency in Python and JavaScript (Svelte/Sveltekit preferred).
• Experience working with scientific or technical datasets.
• Experience with SQL and relational databases.
• Experience with data visualization and dashboard development.
• Strong problem-solving skills and a desire to develop practical solutions for scientific challenges.
• Excellent communication and collaboration skills.
• Ability to work independently while partnering effectively with multidisciplinary teams.

Preferred

• Experience supporting laboratory, research, or scientific environments.
• Experience developing web applications and interactive visualization tools.
• Experience with cloud-based or containerized applications.
• Experience with workflow automation and data pipeline development.
• Familiarity with machine learning, statistics, or scientific data analysis.
• Experience with version control systems such as Git.