Charting New Insights, Navigating Data's Depths
I am a Data Analyst focused on maritime, logistics, and geospatial data. With a background in archaeology and a strong interest in the maritime domain, I work on transforming complex datasets into actionable insights using GIS, data analytics, and machine learning.
My current focus includes: - Maritime data analysis (AIS data) - Geospatial analysis (GIS) - Machine learning for anomaly detection - Data visualization and reporting I am currently building applied projects and continuously developing my technical skills, with the goal of contributing to data-driven decision-making in real-world environments. I am open to remote opportunities in data analysis and related fields.
Data Analytics, GIS & Machine Learning
I work at the intersection of data analysis, geospatial intelligence, and machine learning, transforming raw datasets into structured, decision-ready insights.
AI & Machine Learning
Transforming Data into Predictive Intelligence
I apply machine learning techniques to detect patterns, identify anomalies, and support risk-based decision systems.
- Anomaly detection using unsupervised models (e.g. Isolation Forest)
- Risk scoring and classification systems
- Feature engineering for predictive workflows
Data Annotation & Data Engineering
Turning Raw Data into Structured Insights
I prepare and structure datasets to make them usable for analysis and machine learning pipelines.
Data cleaning and preprocessing
Feature engineering
Dataset integration from multiple sources (AIS, weather, maintenance)
Maritime Data Analysis
Unlocking Insights from Maritime Operations
I analyze vessel activity, operational behavior, and environmental factors to extract meaningful insights.
- AIS data analysis (vessel tracking and movement patterns)
- Operational and environmental correlation analysis
- Identification of high-traffic routes and activity zones
Geospatial Analysis (GIS)
Mapping Data into Spatial Intelligence
I use GIS tools to analyze spatial relationships and visualize maritime patterns.
- Route mapping and vessel trajectories
- Port activity analysis
- Spatial clustering and density visualization
HarborFlow – Maritime GIS & AI Analysis
Flagship Project
HarborFlow is a maritime data analytics project that integrates AIS tracking data, environmental variables, and GIS-based analysis to generate insights into vessel behavior, route patterns, and operational risk.
Built with Python and geospatial tools, the project demonstrates an end-to-end workflow including data ingestion, cleaning, spatial analysis, and dashboard visualization.
The goal is to support data-driven decision-making in maritime and logistics contexts by identifying anomalies, visualizing traffic patterns, and highlighting risk-prone behaviors.
Fuel & Engine Health Analyzer – Yacht Edition
Demo Project
A demo project exploring how engine and fuel data can be used to monitor performance, fuel efficiency, and operational reliability in motor yachts (18–40 meters).
The project focuses on identifying patterns related to fuel consumption, engine behavior, and common operational inefficiencies such as prolonged idling and irregular start conditions.
Through data analysis, the goal is to highlight how structured engine data can support early detection of anomalies, improve fuel efficiency, and reduce the risk of unplanned maintenance.
Key contributions:
- Data cleaning and preprocessing of heterogeneous datasets
- Exploratory analysis of sales trends, routes, and maintenance patterns
- Identification of correlations and operational insights
- Early-stage feature engineering for predictive modeling
- Structured workflow for future scalable analysis
Yacht Data Insights
Case Study
A data analysis case study focused on yacht-related datasets, including sales data, route patterns, and maintenance records.
The project demonstrates a structured approach to data cleaning, exploratory data analysis (EDA), and the initial stages of predictive modeling.
Rather than focusing on final model performance, the emphasis is on methodology: preparing messy datasets, identifying trends, and extracting meaningful insights that could support decision-making in maritime and yacht operations.
Key contributions:
- Data cleaning and preprocessing of heterogeneous datasets
- Exploratory analysis of sales trends, routes, and maintenance patterns
- Identification of correlations and operational insights
- Early-stage feature engineering for predictive modeling
- Structured workflow for future scalable analysis
Collaborations
Collaborations in Maritime Data, GIS, and Analytics
I am open to collaborating with individuals and teams working at the intersection of maritime data, geospatial analysis, data science, and machine learning.
I focus on applying data-driven approaches to real-world maritime challenges, particularly in areas involving AIS tracking, vessel operations, and maintenance data.
I can contribute to projects involving data cleaning, exploratory analysis, feature engineering, and the development of analytical or early-stage predictive models. I am especially interested in work that improves operational efficiency, supports better decision-making, and promotes more sustainable maritime practices.
Areas of interest include:
- AIS & Geospatial Analysis – vessel movement analysis, route patterns, and port activity
- Operational & Maintenance Analytics – analyzing logs and performance data to identify inefficiencies and potential issues
- Predictive & Exploratory Modeling – early-stage models for risk signals, behavior patterns, and operational insights
- Route & Efficiency Analysis – incorporating environmental factors such as weather and congestion
- Data Systems & Quality – working with structured and unstructured datasets, ensuring consistency and usability
- Maritime Sustainability – applying data analysis to support more efficient and environmentally conscious operations
- Open-source & Research Collaboration – contributing to GitHub/Kaggle-style projects in maritime or geospatial domains
I am open to discussions around data projects, collaborations, and junior opportunities in data analytics.
If you are working on something in maritime, logistics, GIS, or data-driven operations, feel free to reach out.
