11/12/2026 updated
100 % available
Economist & Data Scientist | Pricing, Forecasting & Machine Learning | Ex-Principal & Team Lead
Prague, Czech Republic
Worldwide
Doktor der Wirtschaftswissenschaft, Martin Luther University of Halle-Wittenberg, GermanyAbout me
I’ve spent 10 years using data to answer business questions: churn and marketing efficiency at Pipedrive (SaaS), forecasting and customer segmentation at BIKE24 (e-commerce), and price and promotion models at Kraft Heinz. I combine hands-on work with leading small teams.
Machine Learning & Causal Inference
Expertise in machine learning, causal inference, and statistical as well as econometric analysis, applied across e-commerce, SaaS, and CPG industries to improve pricing, marketing, and decision-making.
Pricing & Forecasting Modelling
Development and deployment of price elasticity models, price and promotion optimizers, and forecasting models that have demonstrably improved promotional lift accuracy, capital efficiency, and net sales.
Tech Stack Proficiency
Hands-on experience with Python, SQL, Snowflake, GCP, GitHub, AWS, Airflow, R, EViews, and SAS for building and deploying data science solutions in production environments.
Econometrics & Statistical Analysis
Application of econometric methods including time series techniques and risk modelling for macroeconomic research, ESG scoring, and credit risk assessment.
Customer Segmentation & KPI Development
Building customer segmentation models and establishing KPIs such as retention rates to support strategic decision-making and enable tailored marketing campaigns.
SEM Bidding & Marketing Optimisation
Development and deployment of ML models for SEM Bidding, achieving significant improvements in marketing efficiency.
Agile Delivery & Team Leadership
Leading and mentoring data science teams, driving transitions to agile delivery, and providing cross-functional guidance and stakeholder alignment.
Risk Assessment & Modelling
Performing risk assessment, aggregation, and modelling including credit risk and portfolio stress-testing in financial and pharmaceutical industry contexts.
Expertise in machine learning, causal inference, and statistical as well as econometric analysis, applied across e-commerce, SaaS, and CPG industries to improve pricing, marketing, and decision-making.
Pricing & Forecasting Modelling
Development and deployment of price elasticity models, price and promotion optimizers, and forecasting models that have demonstrably improved promotional lift accuracy, capital efficiency, and net sales.
Tech Stack Proficiency
Hands-on experience with Python, SQL, Snowflake, GCP, GitHub, AWS, Airflow, R, EViews, and SAS for building and deploying data science solutions in production environments.
Econometrics & Statistical Analysis
Application of econometric methods including time series techniques and risk modelling for macroeconomic research, ESG scoring, and credit risk assessment.
Customer Segmentation & KPI Development
Building customer segmentation models and establishing KPIs such as retention rates to support strategic decision-making and enable tailored marketing campaigns.
SEM Bidding & Marketing Optimisation
Development and deployment of ML models for SEM Bidding, achieving significant improvements in marketing efficiency.
Agile Delivery & Team Leadership
Leading and mentoring data science teams, driving transitions to agile delivery, and providing cross-functional guidance and stakeholder alignment.
Risk Assessment & Modelling
Performing risk assessment, aggregation, and modelling including credit risk and portfolio stress-testing in financial and pharmaceutical industry contexts.
Experience
Professional experience0 - 5 years
Freelancer since2026
Languages
GermanNative speakerEnglishFluent
Project history
Re-engineered price elasticity models for US retail using econometric methods, improving promotional lift accuracy by approximately 15% while reducing manual inputs and model runtime. Made the price and promotion optimizer competitor-aware, enabling revenue managers to test pricing responses to competitor moves within business constraints. Mentored Senior Individual Contributors and drove the team's transition to agile delivery.
Led the development and deployment of an ML model for SEM Bidding, driving a 40% improvement in marketing efficiency. Managed and mentored a team of three Data Scientists. Guided the transition from manual, Excel-based KPI forecasting to a fully automated approach using a foundation model. Identified leading churn indicators using causal inference to evaluate the effects of product enhancements.
Provided company-wide leadership in data science projects, guiding cross-departmental decisions. Collaborated within a cross-functional team to develop pricing strategies, resulting in a 20% increase in net sales. Led the development of a forecasting model that enhanced capital efficiency by nearly 30%.