The proven scorecard template to hire top startup product talent

Product talent, both Individual Contributors (IC) and Managers, are vital to iterating on your products’ value for customers. When you’re growing fast a mis-hire in these roles can flatten your company's trajectory toward the moon. Don’t let that happen with Yobs Interview Kits.

What's a Yobs hiring scorecard?

The Yobs Product Interview Kits are built around competencies predictive of success in Product. Each kit includes a scorecard with (a) definitions of the competencies, (b) interview questions in the context of Product and if relevant managing a team, and (c) signals to look for in a candidate’s interview answers.

Some competencies are more important than others when predicting performance, depending on the responsibilities of the job.

The Product Individual Contributor (IC) Interview Kit focuses on the competencies that matter the most.

Conscientiousness

Hard working and orderly

Dutiful

Honest and sincere

Disciplined

Pays attention to details

Courage

Volunteers for challenges

Openness

Handles change

Download the Startup Product Scorecard

Relevant Job titles

The following job titles are especially relevant to the Product Individual Contributor Interview Kit.

The Product Manager Interview Kit focuses on the competencies that matter the most.

Customer Focus

Builds strong customer relationships

Strategic Mindset

Translates vision to strategy

Develops Talent

Coaching and developing others

Ambitious

Sets and achieves goals

Being Resilient

Overcomes obstacles

Relevant Job titles to Product Manager Interview Kit

The following job titles are especially relevant to the Product Manager Interview Kit.

Interview kits include a balance of behaviorally- and scenario-based questions. On one hand, past behavior predicts future behavior and future performance. On the other hand, scenario-based questions are more flexible and future-facing to allow candidates to shoot their shot. Taken together, evidence supports a blend of multiple methods to optimize for predicting on-the-job success for Product Individual Contributors.

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