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Data & ML Engineer | Mathematican | Consultant ⚡Lightning-Fast Data Insights⚡
AI is analyzing your overall score…
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
drjve AG
Data Scientist
June 29, 2026 – Present
verdict
February 24, 2026 – Present
Verdict is an automated system that evaluates LLM outputs at scale, tracks quality metrics over time, detects regressions across model versions, and triggers alerts — all natively on Databricks.
View Projectspark-fuse
September 4, 2025 – Present
spark-fuse is an open-source toolkit for PySpark — providing utilities, connectors, and tools to fuse your data workflows together.
View Projectmicrosoft-fabric-data-platform-template
June 3, 2025 – August 6, 2025
A GitHub starter repository for building modern Data Engineering, ML, and AI solutions on Microsoft Fabric. Includes medallion architecture (Bronze → Silver → Gold), Spark Notebooks, dbt, MLflow, GitHub Actions CI/CD, and arc42-based documentation.
View Projectbluebrick
May 27, 2025 – September 8, 2025
Azure Databricks blueprint with Terraform + GitHub Actions
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong interest and initiative in the data science and engineering domain, aligning well with a target role of Data Scientist. The diversity of projects, ranging from data platforms to LLM evaluation and PySpark toolkits, indicates a broad technical curiosity and a willingness to explore different facets of data science. The open-source contributions suggest a collaborative and community-oriented mindset. However, the candidate's experience level is listed as 0, which might indicate a lack of professional experience despite the impressive personal projects. The single professional experience listed has a future start date, making it difficult to assess actual professional cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and innovative approach to problem-solving, particularly in developing reusable tools and automated systems. The focus on open-source contributions suggests a collaborative mindset. However, without specific psychometric or English test results, a detailed assessment of communication clarity, logical reasoning, work attitude, stress handling, and team collaboration is not possible.