SR Business Analyst Multi-Omics Data Modalities

Job Description :
The Multimodal Discovery Platforms team supports digital platforms that enable multimodal discovery across genetics, omics, spatial biology, digital pathology, high-content imaging, flow cytometry, and medical imaging. The platform team collaborates with ReDev scientist to build scalable, AI-ready digital platforms that accelerate target discovery, biomarker research, translational science, RNAi discovery and delivery, and preclinical development.
As a Business Analyst, you will serve as the strategic bridge connecting wet-lab scientists, computational biologists, and data platform engineers. You will be responsible for translating complex biological workflows spanning single-cell omics, spatial transcriptomics, high-content imaging, and proteomics into clear technical specifications, structured user stories, and business capability and architecture diagrams.
Key Responsibilities
• Business Process Mapping: Engage directly with cross-functional biology and translational teams to map end-to-end workflows and data lifecycles. Map current-state versus future-state data flows
across cloud analytics workspaces, identifying friction points in data ingestion, processing, and downstream visualization.
• Requirements Translation: Convert scientific use cases and analytical bottlenecks into structured epics, detailed user stories, and system workflow diagrams for platform and data engineering teams.
• Delivery Management: Maintain and groom the team's backlog, managing sprint goals and execution cadence in collaboration with the Platform Lead.
• Application Enablement: Develop clear user documentation and IT SOP to drive platform adoption across scientific end-users.
Key Qualifications
• Education: B.S. or M.S. in Bioinformatics, Computational Biology, Life Sciences, Information Technology, or a related field.
• Experience: 3–5+ years as a Business Analyst, Systems Analyst, or Technical Product Analyst in a biotech, pharmaceutical, or life sciences research organization.
• Domain Expertise: Strong familiarity with multi-omics data modalities (e.g., scRNA-seq, spatial omics, proteomics, pathology) and biological assay workflows. Expert in technology with background in bioinformatics or biomedical engineering.
• Core Technical & Methodological Skills:
o Demonstrated mastery of Agile/Scrum delivery using Jira and Confluence.
o Proficiency with workflow mapping tools (Visio, Lucid, Draw.io).
o High-level understanding of cloud-native data platforms (e.g., AWS, Databricks, Snowflake).
• Communication & Collaboration: Outstanding ability to translate fluently between bench/computational scientists and software engineering teams.