Turning Maritime Data into Actionable Intelligence
Data Analyst focused on maritime, logistics, and geospatial intelligence, building data-driven systems and analytical tools.
My work focuses on transforming complex datasets into actionable intelligence, with a particular focus on maritime and geospatial data. I combine data analysis, GIS, and machine learning to explore vessel behavior, traffic patterns, and operational risk, building systems that support real-world decision-making. Current focus: Maritime data analysis (AIS vessel tracking) Geospatial analysis (GIS) Anomaly detection and risk modeling Data visualization and analytical reporting I am currently developing independent projects in the maritime intelligence space, with the goal of building practical tools for shipping, logistics, and data-driven operations. Open to collaborations and early-stage use cases in maritime and logistics.
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 Intelligence System
AIS-based analytics for vessel tracking, port activity, and operational risk.
HarborFlow is a maritime intelligence system that transforms AIS tracking data and geospatial information into actionable insights on vessel behavior, traffic patterns, and operational risk.
It integrates data processing, spatial analysis, and machine learning to detect anomalies, monitor port activity, and uncover patterns that are not immediately visible in raw maritime data.
Designed as a lightweight analytics layer over complex AIS datasets, HarborFlow supports data-driven decision-making in shipping and logistics contexts.
Currently testing with early users in shipping and logistics.
Early-stage maritime intelligence system for analyzing vessel traffic, port activity, and operational risk.
Currently being tested with real-world use cases in shipping and logistics.
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
Maritime Data, GIS, and Analytics
I collaborate with individuals and teams working at the intersection of maritime data, geospatial analysis, and data science.
My focus is on applying data-driven methods to real-world maritime and logistics problems, particularly using AIS data, operational datasets, and geospatial systems.
I work across the full analytical workflow, from data cleaning and exploratory analysis to feature engineering and early-stage modeling, with a focus on generating actionable insights.
Areas of focus include:
- AIS & geospatial analysis (vessel tracking, routes, port activity)
- Operational and maintenance analytics (efficiency and performance signals)
- Risk and anomaly detection using data-driven methods
- Route optimization and environmental impact analysis
- Data systems and pipeline quality for structured analysis
- Maritime and logistics intelligence applications
I am particularly interested in projects that improve operational efficiency, support decision-making, and apply analytics to real-world maritime systems.
If you are working on maritime, logistics, GIS, or data-driven operations, I am open to collaboration and project-based discussions.
