Associate Scientist, Computational Biology

Cabaletta Bio•Philadelphia, PA

2d•Hybrid

About The Position

The Associate Scientist, Computational Biology will build and maintain programmatic and agentic workflows that clean, transform, and merge large, feature-rich datasets — primarily flow cytometry, MSD, and dPCR data — into analysis-ready information. Working under the guidance of senior computational biology staff, they will collaborate with Research, Translational, Manufacturing, and Clinical teams to visualize and correlate data across the organization, surface key scientific questions, and communicate clear summaries of their analyses to stakeholders.

Requirements

MS in computational biology, bioinformatics, computer science, or a related field plus 1–2 years of relevant experience; or a BS with additional demonstrated experience in computational and programmatic analysis of biological data.
Strong foundation in computer science, statistics, mathematics, and biology.
Proficient in Python, with experience building automated scripts or pipelines.
Demonstrated ability to integrate, mine, analyze, visualize, and interpret data using computational and statistical tools.
Meticulous and detail-oriented, with the ability to follow complex operating procedures (SOPs) and thoroughly document work.
Strong team orientation and a passion for continuous self-development.

Nice To Haves

Experience designing agentic or LLM-driven workflows — whether through structured instructions/prompts, orchestration frameworks (e.g., LangChain, AutoGen), or direct API integrations.
Familiarity with software engineering best practices (e.g., version control/Git, code review, testing).
Familiarity with cloud computing environments (AWS, GCP, or Azure) and workflow orchestration tools (e.g., Airflow, Nextflow).
Experience with data analysis and machine learning techniques.
Experience with traditional bioinformatics analysis (e.g., genomic, transcriptomic, or proteomic data) and multi-omics data integration.
Experience in an industry or startup setting is preferred.

Responsibilities

Design, build, and maintain programmatic and agentic workflows to support recurring computational biology tasks, including cleaning, transforming, and merging large-scale biological datasets with many features.
Mine public and internal databases for relevant biological and disease-related information.
Develop and automate interactive data visualizations and dashboards.
Perform correlative analyses and produce clear, intuitive summary reports of data exploration and analyses for scientific and non-scientific audiences.
Communicate results and recommendations to stakeholders, including scientific colleagues and collaborators.
Maintain thorough documentation of workflows and analytical methods in accordance with SOPs.