We are a technology partner for life sciences companies, delivering open-source AI, R and Python solutions, cloud-based statistical computing environments, and SAS-to-Open Source migration to accelerate drug development in regulated settings.
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Pros: The remote-first setup is genuinely excellent, offering great flexibility for life balance. I've had the chance to work on diverse and complex data science projects for various clients, which really pushed my skills in machine learning and AI. The culture encourages continuous learning and professional development, especially within the R and Python ecosystem. It's a great environment for staying current in the data science field.
Cons: While communication tools are in place, sometimes it feels like there are gaps in syncing between different project teams or departments, especially when working asynchronously. This can occasionally lead to duplicated effort or minor delays. More structured, cross-functional check-ins could really help streamline operations and ensure everyone's on the same page.
Advice to Management: Consider implementing more regular, structured cross-team sync meetings to enhance collaboration and information flow among distributed teams working on client projects.
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What is the interview process like at Appsilon for a Data Scientist role in Poland?
My interview experience at Appsilon for a Data Scientist position in their Krakow office involved a technical screening, followed by coding challenges and discussions about my past projects. The team was very professional and focused on assessing my problem-solving skills relevant to their custom R and Python solutions for clients in the finance and tech industries.
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