About

I am a strategic leader with over 12 years of experience driving business growth, operational excellence, and digital innovation across diverse industries. Passionate about fostering a culture of innovation and leadership, I have successfully built and led high-performing teams that deliver measurable business results. I have also trained over 150 professionals in Data Science and AI and lectured more than 100 graduate and PhD students. Currently, I serve as Head of Data Science and AI at voestalpine High Performance Metals DIGITAL SOLUTIONS, where I hold full P&L accountability and oversee strategic leadership and resource allocation.

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Forums

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15d ago

How do you catch silent data corruption bugs early?

Visual bugs or broken buttons are easy to spot right away, but silent failures are terrifying because everything looks completely normal on the dashboard.

Our scariest silent bug happened when a background worker quietly stopped processing webhook retries due to a silent timeout exception leaving hundreds of user orders stuck in limbo for days without any logs throwing an alert. We ended up setting up an external health ping just to make sure those queues are actually moving every hour. What's your go to way for catching background failures before users notice?

Should AI share of voice become a marketing KPI?

With over 60% of searches ending without a click, search performance reporting needs to account for what users see directly in search results.

Think about someone researching CRM software. They might ask ChatGPT for vendor recommendations, compare pricing, and evaluate features before visiting a single website. The brands appearing throughout those conversations have an opportunity to influence the buyer's shortlist.

W41 Product Update: Choose which languages get human review

You can now send translations to human review only when they re in a language you select and score below your quality threshold. All others continue without human review.

Keep human review to selected languages

You could already use a quality threshold to send low-scoring translations to human review. Now you can narrow that rule to selected languages within the same localization engine.

For example, when introducing Japanese or working through terminology issues in German, you can send low-scoring translations in those languages to a reviewer. Translations that meet your threshold continue automatically, and your other languages skip human review.

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