IntermediateBEHAVIORAL
In your previous work as a business analyst with scientific or R&D stakeholders, describe a specific project where you gathered requirements from bench scientists around registering biological entities (e.g., cell lines, samples, or compounds). How did you translate their experimental language into precise data and process requirements for an inventory or registration system?
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General

Sample Answer

At my last company, I partnered with about 25 oncology bench scientists to redesign how they registered engineered cell lines. Their language was all about “my CRISPR batch,” “the parental line in the -80,” or “the vial with the good phenotype,” which didn’t map cleanly to our inventory system. I started by shadowing three teams at the bench for a week and sketching their actual workflows from thaw to assay. In workshops, I had them walk through recent experiments and I kept asking, “What would you need to find this again six months from now?” and “What makes two ‘similar’ lines actually different for you?” Out of that, I defined clear entities (parental line, derived line, vial, aliquot) and mandatory attributes like species, passage number, modification type, construct ID, and QC results. We converted their shorthand (e.g., “HER2 KO pool 3”) into controlled vocabularies and drop-downs. After rollout, registration completeness went from ~55% to 93%, and time-to-find a line in the system dropped by about 40%, based on search logs and a follow-up survey.

Keywords

Shadowed bench scientists and used their real workflows to drive requirementsTurned informal experimental language into well-defined entities and attributesIntroduced controlled vocabularies and structured fields instead of free textMeasured impact via registration completeness and search-time reduction
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