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TRR - UX designer ⎯ web app

AI suggestions how to match your CV to a specific job

I led research to uncover job seekers' challenges through interviews, data analysis, and ATS reviews, shaping a focused “How Might We” question for a design sprint. I facilitated ideation workshops, driving solutions aligned with user needs and business goals. During prototyping, I designed an intuitive tool to match job ads with user CVs, collaborating with developers to refine and test a functional prototype. This ensured the solution was user-friendly, technically feasible, and effective in real-world scenarios.
TRR - UX designer ⎯ web app

AI suggestions how to match your cv to a specific job

I led research to uncover job seekers' challenges through interviews, data analysis, and ATS reviews, shaping a focused “How Might We” question for a design sprint. I facilitated ideation workshops, driving solutions aligned with user needs and business goals. During prototyping, I designed an intuitive tool to match job ads with user CVs, collaborating with developers to refine and test a functional prototype. This ensured the solution was user-friendly, technically feasible, and effective in real-world scenarios.
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Background
Job searching was time-consuming for applicants, as each application required a tailored CV to highlight the strengths and experiences most relevant to the specific role. Through interviews with job seekers, it became evident that while many found this process challenging, they also recognized that customizing their applications significantly improved their chances of securing an initial interview.

However, uncertainty and difficulty crafting tailored applications led many to frequently seek TRR’s assistance with individual documents.
We aimed to streamline the customization process for job applications and reduce the number of related support requests. This allowed us to focus more on guiding laid-off employees to regain confidence and advance their careers.
My contribution in this initiative
  • Research and define
    During the research phase, I led the effort to gather insights through interviews with job seekers, aiming to understand their challenges in the job application process deeply. I also analyzed data from major external insight reports and conducted an in-depth review of ATS (Applicant Tracking System) screening mechanisms to identify barriers candidates face.

    Building on these insights, I crafted a How Might We (HMW) question that captured the core problems uncovered during research. This HMW question served as a foundation for the next phase, driving the focus and direction of the upcoming design sprint.
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  • Ideation
    During the ideation phase of the design sprint, I led the preparation and facilitation of brainstorming sessions, fostering cross-functional collaboration to generate diverse ideas aligned with user needs and business goals. I ensured the sessions were structured to encourage creativity while staying focused on the core challenges identified during research. Together, we narrowed to solutions that directly addressed key user pain points.

    This process laid a strong foundation for prototyping, shaping the direction of the design concept
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  • Prototyping
    During the design sprint, we decided to develop a solution that analyzed a specific job ad against the CVs users had uploaded to their Matching Profiles. I was responsible for designing the concept and user experience, ensuring the process was intuitive and seamless for users.

    While I focused on crafting the user journey and interface, the developers worked on a proof of concept (PoC) for the technical solution. We collaborated closely throughout, continuously refining and adapting the design based on insights and feedback from the PoC. This iterative approach ensured the solution was both technically feasible and aligned with user needs.
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  • Testing the solution
    Normally, I conduct usability tests using prototypes created in Figma. However, we developed a functional prototype instead because the experience we wanted to explore could best be evaluated by generating unique suggestions for a specific user and job ad. Based on our PoC and the rapid development of this feature, we were able to build a testable solution quickly.

    This approach allows us to gather more realistic user feedback and ensure the solution performs as intended in real-life scenarios.
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Get AI suggestions how you can improve your applicaton documents for a specific job