Before we meet
Behind the resume.
A quick overview of how I work, think, and collaborate
How I approach design
I start by identifying the problem, whether it comes from research or is presented by the team. Then I focus on solutions, mechanics, and user flows, working with drafts and concepts rather than high-fidelity designs. I collaborate closely with engineers throughout to ensure ideas are technically feasible. Once we agree on a direction, I move into design and prototyping, and before shipping, I make sure the experience is clear and correctly implemented. I stay involved during the build to validate quality and ensure the final product meets both user and business needs.
Solving real product problems
At awork, we noticed a drop-off right after sign-up. In the mobile app, we had a screen telling users that the experience was better on a computer, and we sent them an email with a link to log in there. But almost nobody was clicking the email. I realized that if someone is signing up on their phone, they probably aren't sitting near a computer at that exact moment. So, instead of just sending the email immediately, we gave them options. We asked: 'When do you want to receive this link?' They could choose 'Right now,' 'In 4 hours,' or 'Tomorrow morning.' By letting them choose the moment they knew they’d be at their desk, our second-session rate grew to 100%, and the desktop subscription ratio jumped to nearly 7%.
Collaboration & alignment
I work closely with PMs and engineers daily, and involve teams like Customer Success or Marketing when needed. I also use workshops to align early — bringing stakeholders together around the problem helps reduce friction later and leads to better, faster decisions.
About me
I’ve worked across e-commerce, B2B SaaS, and growth. I combine qualitative research, data analysis, and experimentation to iterate on key product flows and improve metrics such as activation, feature adoption, and conversion. I work closely with product, engineering, and business teams to take initiatives from initial problem definition through implementation and impact measurement. Most recently I was a Product Designer in Growth at awork, a B2B SaaS company in Germany, where I owned the onboarding and activation experience. I ran experiments and conducted 100+ user interviews to improve product adoption, including increasing onboarding completion and usage of our AI feature. Before that I worked at Mercado Libre, one of the largest e-commerce platforms in Latin America, designing experiences across five markets. That experience taught me how to balance user needs, business goals, and technical constraints at scale.
Using data to drive decisions
I gather feedback through surveys and interviews, and once I have the data, I like to use FigJam to cluster ideas or even share data with ChatGPT to find patterns quickly. I then prioritize everything using a matrix like ICE or MoSCoW to decide what to build first. My toolset has changed a lot with AI. I still start with hand drafts and sticky notes, but now I use **Lovable** to turn my mechanics and flows into quick prototypes. It helps me show the team how an idea works and feels before I ever touch a pixel in Figma. It saves me so much time because I can catch logic errors early, when they are still 'cheap' to fix.
Working through disagreements
On one onboarding project, I proposed adding a leaderboard to the post-subscription onboarding screen. The goal was to create healthy competition and make the setup feel more like a team effort, which I believed would boost completion rates. Some stakeholders resisted, thinking a leaderboard didn’t fit our professional tool and wouldn’t actually motivate users. Rather than arguing, I took a few days to gather real evidence. I ran quick user interviews using a simple screenshot of the concept. The feedback was overwhelmingly positive—users enjoyed seeing where they stood compared to peers and felt more motivated to complete the tasks. I shared these insights with the stakeholders, and once they saw the user perspective, they agreed to move forward. After implementing the leaderboard, onboarding completion doubled, showing the value of combining user-centered design with data-driven persuasion. This experience reinforced my approach of turning disagreements into opportunities to validate ideas with users.
A lesson from a failed experiment
At awork we tried to increase upgrades for a new “Docs” feature by adding a “Request this from your Admin” button for users. It didn’t work. The upgrade rate stayed the same because the experience created a broken feedback loop: users took an action with no immediate value, and admins received notifications that felt like noise. It taught me that in product design showing value through experience is far more effective than asking for it.
How I think about Iteration
I don’t follow a fixed number of iterations — I iterate until the risk is low enough to build. Typically, I move from: Low-fi (align on logic) Mid-fi (test interactions) High-fi (final polish and handoff) The goal is to fail fast early, so we don’t pay the cost later in development.
Testimonials
What my coworkers say.
Real stories from people we've had the pleasure of working with.
