Data Scientist — Engineer
Søndervigvej 48, Vanløse, Denmark
📞 +45 42 65 65 74
📧 [email protected]
🔗 LinkedIn
With 10+ years of experience spanning data science, engineering, and product development, I excel at transforming complex data into impactful AI solutions and driving digital initiatives from concept to deployment. My background includes significant hands-on experience in cloud environments (GCP/AWS), geospatial analysis, and IoT data. I have a proven track record of leading the development of new data products, prioritizing features, and ensuring that delivered solutions provide clear business value.
Languages
Python (Pandas, Scikit-learn, GeoPandas, Shapely, Pyproj, Folium, Osmnx), Matlab, SQL, R, Bash, HTML, Java/Javascript (familiarity)
Tools
Git, Docker, Kubernetes, DBT, BigQuery, MongoDB, Jupyter, Lambda, CI/CD, PowerBI, Looker Studio
Platforms
GCP (advanced), AWS (advanced), Azure (basic)
ML Techniques
Data Modeling, ETL, Feature Engineering, Clustering (DBSCAN), Boosted Trees, Kalman Filtering, API (REST, FastAPI, OpenAPI)
Methodologies
Agile Development, Opportunity Solution Trees
- Developed and applied advanced analytical techniques for complex spatial and temporal data, including GPS trajectory analysis and network analytics.
- Led technical initiatives involving complex algorithms for large-scale infrastructure datasets.
- Contributed key data processing and analytical components to a winning tender for a real-time data platform.
- Applied DBSCAN clustering to raw GPS data for customer insights.
- Performed signal processing and pattern recognition on AIS streaming data.
- Calibrated simulation models with real-world location data through iterative model tuning.
Copenhagen / Oslo, Denmark / Norway
Jan 2025 – May 2025
- Implemented and deployed anomaly detection models (isolation forest) in AWS.
- Designed customer-facing real-time ML API (Open API + AWS Lambda).
- Validated JSON inputs using Pydantic models.
- Worked in agile framework using Opportunity Solution Trees (OST).
Copenhagen, Denmark
Feb 2022 – Dec 2024
- Designed, developed, and deployed AI/data solutions on GCP for IoT data.
- Provided mentorship and best practices for data pipelines and structuring.
- Built ETL pipelines and GCP workflows for anomaly detection.
- Created Kalman Filter algorithm to reduce device calibration time (30 min → 30 sec).
- Built DBSCAN-based clustering for customer behavior analysis.
- Collaborated with analytics/product teams to align insights with customer solutions.
Lyngby, Denmark
Feb 2021 – Feb 2022
- Defined requirements and processed global AIS data in GCP.
- Led AI model development for MVP bunkering detection system (F1 > 0.8).
- Prioritized MVP features by product alignment and technical feasibility.
Lyngby, Denmark
Feb 2016 – Feb 2021
- Delivered data processing/analysis for transportation modeling projects.
- Handled full data lifecycle from ingestion to model-ready outputs.
- Part of winning Danish Road Directorate tender team.
- Conducted statistical analysis for infrastructure impact assessments.
- Developed Azure BI integrations for data visualization.
Copenhagen, Denmark
Apr 2015 – Nov 2015
- Collaborated with Google X on spatial calibration of traffic simulation models.
Lyngby, Denmark
Feb 2013 – Feb 2016
- Supported ingestion and validation for Danish national transportation model.
Washington, DC, USA
1996 – 2006
- Managed high-availability Oracle and MS SQL databases.
- PhD, Civil Engineering (Transportation) — University of Virginia, Aug 2012
- MS, Civil Engineering — University of Virginia, Aug 2009
- BS, Civil Engineering — Carnegie Mellon University, Apr 1993
- Winner, ABJ70 Transportation Data Forecasting Competition (Predictive Accuracy), Fall 2012
- 2012 — Development of a Travel Time Data Quality Hypothesis Test, Transportation Research Record No. 2308
- 2011 — Network Stratification Method to Classify Links by Travel Time Variation, Transportation Research Record No. 2256