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  <url>
    <loc>https://www.lea.show/me/more/about/you</loc>
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    <lastmod>2023-10-21</lastmod>
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      <image:title>about - Hello, I’m Lea.</image:title>
      <image:caption>I plan and manage research studies to help build human-centered interfaces. This spans from discovery research to requirement engineering. With this, I help my teams create human-centered design solutions, make data-driven business decisions, and measure customer success. My designs move mobility, help people to better understand and manage their insurance, improve the employee experience of millions, and bring awareness to climate change. If you are curious about me:</image:caption>
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  <url>
    <loc>https://www.lea.show/me/what/you/do</loc>
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    <lastmod>2023-10-21</lastmod>
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  <url>
    <loc>https://www.lea.show/me/some/work</loc>
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    <priority>1.0</priority>
    <lastmod>2023-10-17</lastmod>
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      <image:title>work</image:title>
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  <url>
    <loc>https://www.lea.show/me/predictive/analytics/software/solutions</loc>
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    <priority>0.75</priority>
    <lastmod>2020-03-04</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5e2b09819ecafb627b60d333/1581072564304-17W5K59SWC9IQPK7BDFR/image-asset.jpeg</image:loc>
      <image:title>predictive analytics - Filter data sets &amp; navigation</image:title>
      <image:caption>A Key insight was to enable the engineers to not just have a selected view of the data in shape of a simple graph but to dive deep into the data. What I see young designers doing wrong with dashboards is that they create visually appealing and simple dashboards with a selected range of pretty graphs which wouldn’t do much good to the usability. I held workshops with focus interviews with the engineers to understand their key pain: a system which enables them to dive deep into their data and find patterns or trends. Most available CSS graph libraries have such features but we eventually decided on an easy to implement library which was able to be fed though python — allowing the data scientists on the team to prepare the data sets.</image:caption>
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    <image:image>
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      <image:title>predictive analytics - Data Science powered by sovanta AG</image:title>
      <image:caption>It was a great benefit to the project and its quality to have the scientists work on the code instead of the development team, who would have needed to be trained in the matter of data science prior to their work. I also treasured this time working very close to the data science lab and its scientists since I quickly gained so many insights into statistics and the matter or big data. They shared their love to big Data and patterns. From an initial love for data visualization, a passion for statistics developed. You can read more about data science at sovanta here.</image:caption>
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  <url>
    <loc>https://www.lea.show/me/research</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2020-03-04</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5e2b09819ecafb627b60d333/1581084198788-MPW3JCPSNDJQN73FKY7S/image-asset.jpeg</image:loc>
      <image:title>product research - Research and its effect on product development</image:title>
      <image:caption>At the beginning of every project stands the planning of strategy and research. This can only be achieved with a clear understanding of the situation and challenges at hand. Approaching a project with provisional personas and an unclear vision is common. I encountered many clients over the past years to mainly struggle with the endeavour of software development itself. Sure their vision can be too big for a close deadline, but helping them with a lean approach to their product will eventually lead to success. One of the core elements of the build-measure-learn cycle are decisions based on validated user research — measure the success of differing user behaviour within your product and your can create a Killer UX!</image:caption>
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  <url>
    <loc>https://www.lea.show/me/that/interactive/exhibit</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2020-03-04</lastmod>
    <image:image>
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      <image:title>interactive exhibit - A diverse team &amp; subject matter experts</image:title>
      <image:caption>The team for this big venture was creative, passionate, and diverse from day one. I was one of ten designers to have supported the design concept, and in many different matters of the craft. One being game design for which we had the game designer Philipp Stollenmayer to consult us. For the technical challenges we were lucky enough to find enough passionate developers in our pool of talents at sovanta AG. To stay scientifically correct we even hired a scientists, with a master degree in geology, to validate the visual design of or dystopian prediction of the future. Even the storytelling and dialogue was assisted through professional help: Falko Löffler helped us to elevate our writing.</image:caption>
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    <loc>https://www.lea.show/illustration</loc>
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    <lastmod>2020-11-28</lastmod>
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      <image:title>Illustration</image:title>
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      <image:title>Illustration</image:title>
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