We’re looking for a data/visualization engineer to help us build tools that transform complex biological data and state-of-the-art models into actionable insights.

You’ll collaborate with cross-functional teams, apply modern data science & visualization approaches, and contribute directly to advancing drug discovery.

The Opportunity

Within this group, you’ll collaborate with a cross-functional team to design, develop, and deploy robust tools that empower scientists to explore, visualize, and interpret complex biological datasets and models—ranging from spatial transcriptomics and high-throughput chemical screens to real-world clinical data. While you won’t be expected to be an expert across the full technology stack, we value fluency across boundaries. Depending on your background, your work may focus more on front-end or backend engineering, and could include:

• Engaging directly with scientists—at the bench or the keyboard—to understand and clarify emerging (and sometimes ambiguous) analytical needs
• Identifying, evaluating, and applying emerging technologies to analyze and visualize biological and chemical data in support of drug discovery and development
• Designing and implementing modular, extensible platforms that allow biologists and data scientists to access, share, and interpret computational results, abstracting technical complexity while enabling scientific insight
• Creating intuitive, interactive visualizations that integrate diverse biological data types (e.g., spatial imaging, transcriptomic, clinical), helping scientists explore hypotheses and uncover insights
• Building scalable, high-performance data pipelines and backend systems, including APIs and services, to efficiently process and deliver large-scale, multimodal biological data.
• Collaborating across distributed scientific, engineering, and design teams to support end-to-end development—from early exploration to production-ready applications

Who you are

• Ph.D. in Data Science, Mathematics, Statistics, Computer Science, Life Sciences, Chemistry, Public Health, or a related field, with 2+ years of relevant experience; alternatively, a Master’s degree with 5+ years of relevant experience
• Strong analytical intuition for extracting meaning from complex datasets, coupled with the ability to communicate insights effectively across disciplines and backgrounds.
• Proficient in using Python and/or R to transform and analyze complex biological datasets, with a solid understanding of software engineering principles such as modular design, testing, and version control in collaborative, production-oriented environments
• Experienced in building static and interactive visualizations using modern libraries and tools (e.g., D3.js, Vega-Lite, WebGPU, Plotly; Shiny, ggplot2; Streamlit, Dash, Altair, Seaborn, Bokeh)
  Preferred expertise building intuitive front-end applications using modern JavaScript or TypeScript frameworks (e.g., Svelte, Vue, React), with seamless integration of interactive web-based visualizations (e.g., D3.js, WebGL, WebGPU)
• Preferred experience in backend development with Python, including building scalable APIs using frameworks such as FastAPI and GraphQL
• Preferred familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes)
• Comfortable collaborating with AI/ML scientists to integrate outputs from machine learning models—such as embeddings, classifications, or generative outputs—into user-facing tools that enable model interpretability and interaction
• Bonus: Experience designing tools or workflows that leverage AI—such as LLMs or agentic systems—to assist with biological data exploration and interpretation
• Curious, eager to grow new skills, and excited to explore emerging technologies while collaborating across diverse, multidisciplinary teams