Freelancer profile translated to English.
Back to original languageAbout Jiangcheng
Data scientist with an MSc Econometrics (UvA) and 3+ years of experience in translating complex business questions into data-driven solutions. Specialized in causal inference, A/B testing, and econometric modeling to quantify price elasticity and the impact of pricing strategies.
At Simon-Kucher, I am working on a data-science-driven revenue management system for a large US real estate investment trust — including demand and supply forecasting, price elasticity, and expiration management, with models production-ready on AWS. Previously, at OZ-Hami, I built an end-to-end forecasting pipeline for logistics planning (6% MAPE, 4 weeks ahead) and a recommender system for a webshop platform.
Strong in the entire process: from ETL pipelines (DBT, Azure/AWS) to statistical validation and clear PowerBI dashboards for stakeholders. Comfortable in Dutch and English-speaking environments, with a consulting background that helps translate technical results into concrete business decisions.
English
Native or bilingual
Dutch
Fluent
Chinese
Native or bilingual
Can work on-site
Enschede (up to 50km)
Experience
- Simon-Kucher,Data Science ConsultantOctober 2025 - June 2026 (8 months)Amsterdam, Netherlands• • Causal Explanation of Anomalies: Core team member on a data-science-driven revenue management system for a leading US real estate investment trust (REIT), researching, designing, and deploying statistical models that explain the causal drivers behind demand, supply, and pricing anomalies.• • Model Lifecycle Ownership: Developed long-term (up to 24-month) demand forecasting models and probabilistic supply/expiration models with simulation components, monitoring performance once in production.• • Production Deployment & Orchestration: Contributed to deployment of production-grade models on AWS (Docker, Airflow), collaborating with engineering on orchestration and monitoring.
- OZ-Hami,Data ScientistJune 2024 - September 2025 (1 year and 3 months)Aalsmeer, NH, Netherlands• • Causal Inference: Designed econometric models to estimate price elasticity and isolate the causal impact of pricing strategies, going beyond correlation to explain the "why" behind observed shifts in customer behavior.• • Experimentation & Statistical Validation: Designed, ran, and monitored A/B tests to validate dynamic pricing strategies, defining success metrics and quantifying business impact before rollout.• • Time Series Forecasting: Owned an end-to-end time series/anomaly-relevant forecasting pipeline for logistics planning, achieving 6% MAPE at a 4-week-ahead horizon.• • Applied Machine Learning: Designed and built a recommender system, applying supervised learning methods to enhance webshop user experience.• • Data Pipelines & Orchestration: Co-engineered scalable ETL/orchestration pipelines using DBT on Microsoft Fabric (Azure) to keep large, complex datasets clean and analysis-ready.
- Mobis Corporate Finance,Data AnalystJune 2022 - May 2024 (1 year and 11 months)Amsterdam, Netherlands• • Statistical Modeling: Developed an NLP-based classification model achieving 96% accuracy using statistical validation and model evaluation techniques.• • Business Analytics: Built automated data pipelines connected to PowerBI dashboards, translating ambiguous business questions into structured analytical solutions.
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Education
- MScUniversity of Amsterdam2024MSc
- BScUniversity of Amsterdam2023BSc