Pascal Debert

As a Data Scientist and AI Engineer, I build scalable microservices using AWS Lambda and Docker on ECS, focusing on generative AI and production ML systems. I manage full ML pipelines—from data extraction (e.g., DynamoDB) and transformation to training, evaluation, and optimization. I also create custom tools like internal R Shiny apps and lead workshops to help colleagues adopt practical AI solutions with tools like Zapier and Slack.

I managed the end-to-end execution of market research projects, serving as the primary methodological consultant for clients. Project Leadership & Consulting: Provided start-to-finish client support, covering methodological consulting, detailed questionnaire conception, operational field support, and final data analysis (qualitative/quantitative). Methodological Development: Actively drove innovation and development of new research methods in collaboration with colleagues to enhance service offerings.

Statistical Analysis (R): Cohort Analysis, data wrangling (Tidyverse), visualization. Built classifiers: Random Forest & XGBoost. AWS Cloud: Managed IAM roles. App deployment via Elastic Beanstalk + DockerHub images. Data visualization in Metabase. Mounted S3 locally. HR Support: Vetting Data Science candidate tasks.

International Talent Acquisition: Managed the initial phases of the recruiting process by conducting qualification and motivational interviews in both German and English. Employee Onboarding: Ensured a smooth and welcoming experience for new hires by overseeing and executing the HR onboarding process for new colleagues. Recruiting KPI Tracking: Monitored and analyzed key Recruiting KPIs to assess pipeline efficiency and inform strategic talent acquisition decisions.

Teaching students to use SPSS for statistical analysis. - Statistical modelling - Linear/Logistic Regression - ANOVA - Exploratory Data Analysis - Plotting

Business Psychology

Personal- und Organisationspsychologie