Interview scorecard template

Biotech Researcher interview scorecard

Evaluate Biotech Researcher candidates across 4 weighted areas: technique and experimental design, results that went somewhere, troubleshooting and reproducibility, and documentation and collaboration. Technique and experimental design leads at 35%, so probe hands-on command of specific platforms: CRISPR editing, qPCR, Western blot, flow cytometry, mammalian cell culture, and how they design. Use the rubric to compare role-specific evidence consistently.

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laboratory applied scienceassay developmentcell culturecrisprmolecular biology
TL;DR
For technique and experimental design, look for evidence the candidate names exact protocols, antibody clones and cell lines used, and justifies control arms, n numbers and statistical power without prompting. For results that went somewhere, look for evidence the candidate traces specific data they generated to a downstream decision, milestone or paper, with dates, collaborators and their own contribution clearly bounded. Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework

What to assess and how to score it

Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.

01
Evaluation factor

Technique and experimental design

35% weight

Probe hands-on command of specific platforms: CRISPR editing, qPCR, Western blot, flow cytometry, mammalian cell culture, and how they design controls, replicates and dose ranges.

Evidence to listen for

  • Runs the assays and instruments themselves rather than describing what a team does
  • Designs experiments with controls, replicates, and a stated hypothesis
  • Knows what each technique can and cannot resolve
  • Understands the science, not only the protocol

Five-point scoring guide

1
Poor

Protocol follower with no experimental design; cannot justify controls.

2
Needs Improvement

Runs standard assays; designs experiments poorly or not at all.

3
Satisfactory

Competent at the bench with sound routine design.

4
Very Good

Designs rigorous experiments and understands the limits of each technique.

5
Excellent

Names exact protocols, antibody clones and cell lines used, and justifies control arms, n numbers and statistical power without prompting.

02
Evaluation factor

Results that went somewhere

25% weight

Ask which of their results advanced a program: a lead candidate nominated, an assay transferred to QC, a patent filing, or a first-author publication.

Evidence to listen for

  • Names projects where their results changed a decision, a process, or a product
  • States their own contribution rather than the group's
  • Has taken something from bench to a larger scale, a filing, or a publication
  • Knows what happened to the work after they handed it over

Five-point scoring guide

1
Poor

No results that went anywhere; work is entirely exploratory.

2
Needs Improvement

Contributed to projects but cannot say what their data changed.

3
Satisfactory

Real contributions; outcomes described loosely.

4
Very Good

Names results that changed a decision, with clear personal scope.

5
Excellent

Traces specific data they generated to a downstream decision, milestone or paper, with dates, collaborators and their own contribution clearly bounded.

03
Evaluation factor

Troubleshooting and reproducibility

25% weight

Test how they chase failing experiments: contaminated cultures, mycoplasma, inconsistent transfection efficiency, drifting standard curves, or a knockdown that will not reproduce across passages.

Evidence to listen for

  • Treats a failed run as information rather than bad luck
  • Isolates reagent, instrument, operator, and biological causes systematically
  • Knows why a result failed to reproduce and can say when their own data was wrong
  • Keeps records good enough to diagnose from months later

Five-point scoring guide

1
Poor

Repeats failed runs unchanged; no diagnostic thinking.

2
Needs Improvement

Troubleshoots by substitution; cannot explain a reproducibility failure.

3
Satisfactory

Solid troubleshooting on familiar assays.

4
Very Good

Systematic isolation of causes, and honest about their own irreproducible results.

5
Excellent

Describes a systematic isolation of variables, records what fixed it, and shows reproducibility data across independent runs or operators.

04
Evaluation factor

Documentation and collaboration

15% weight

Look for ELN discipline (Benchling, LabArchives), SOP authoring, sample and freezer inventory tracking, and how they hand off methods to bioinformaticians or process development.

Evidence to listen for

  • Keeps records to the standard the setting requires, whether that is GLP, GMP, or a defensible notebook
  • Writes up so someone else can repeat the work
  • Works with process, quality, or clinical colleagues rather than in a bench silo
  • Explains a result to a non-specialist without overclaiming

Five-point scoring guide

1
Poor

Records would not survive audit; work is not repeatable from them.

2
Needs Improvement

Documentation is thin; write-ups need heavy editing.

3
Satisfactory

Adequate records and write-ups; collaboration is limited.

4
Very Good

Audit-standard records and clear communication across functions.

5
Excellent

Keeps records another scientist can rerun from, has written SOPs adopted by peers, and communicates raw data caveats honestly.

Evidence-led prompts

Interview questions for a Biotech Researcher

Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.

  1. 01

    Can you provide an example of a challenging research project and how you addressed it?

  2. 02

    Have you authored or co-authored research papers? Can you elaborate on one?

  3. 03

    Can you describe your experience with sequencing technologies?

  4. 04

    Can you describe your experience with cell culture techniques?

  5. 05

    Have you worked with gene-editing technologies?

See the complete Biotech Researcher question set
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