Marijo Alilović, Developer in Zagreb, Croatia
Marijo is available for hire
Hire Marijo

Marijo Alilović

Verified Expert  in Engineering

Data Scientist and Developer

Zagreb, Croatia
Toptal Member Since
June 15, 2022

Marijo is an experienced data scientist with a strong mathematics and mathematical statistics background. He is proficient in statistical analysis, data handling, and optimization techniques and effectively translates complex data into actionable insights, leveraging solid analytical reasoning and precise communication skills. Marijo is detail-oriented, proficient in R, SQL, and Python, and passionate about delivering data-driven solutions across diverse domains.



Preferred Environment

R, RStudio, RStudio Shiny, SQL

The most amazing...

...thing I developed is a tool that enables easy creation of successful and cost-efficient public road testing campaigns for ADAS feature testing.

Work Experience

Data Scientist | Software Developer

2019 - PRESENT
  • Designed and developed a route creation tool that creates routes that maximize ADAS feature-relevant scenarios on public roads. This tool enables conducting successful and cost-efficient public road testing of ADAS features.
  • Created and implemented an algorithm for creating Real Drive Emissions (RDE)-compliant cycles. The algorithm allows optimization of dynamics, and all legislative requirements are user inputs, which makes algorithm adaptable for every market.
  • Implemented a pipeline for importing, tidying, transforming, aggregating, and visualizing vehicle fleet data. Daily reports in HTML and PPTX format are automatically created based on the pipeline.
  • Designed and implemented a tool for data enrichment. The tool gives an interface for including APIs into the workflow for querying for additional metadata used in later analysis.
  • Built interactive graphical user interfaces (GUIs) for various projects I've worked on: route creation tool, vehicle fleet monitoring, and Real Drive Emissions (RDE) cycle.
Technologies: R, RStudio Shiny, SQL, Python, Data Science

College Assistant

2017 - 2019
University of Zagreb
  • Created scripts and instructional materials for various mathematical subjects, ensuring clarity and accessibility for students. These materials enhanced the learning experience and contributed to student engagement and comprehension.
  • Designed a comprehensive introductory math curriculum from scratch. This resulted in the successful rollout of a structured program that introduced fundamental mathematical concepts to students, laying a solid foundation for their academic journey.
  • Demonstrated a measurable impact on student performance by implementing engaging teaching techniques. This is evidenced by consistently high student evaluations and improved exam scores.
Technologies: R, Python, Statistics

Real Drive Emission Cycle Generator
An algorithm for generating Real Drive Emissions (RDE) cycles using driven data. All legislative requirements are user inputs. It is possible to optimize for high or low dynamic cycles where one the dynamic parameters is near its boundary limit.

Optimized Route Generator
I developed a tool that creates routes within user-specified boundaries to maximize scenario coverage for testing Advanced Driver Assistance Systems (ADAS) on public roads. This includes a route generation algorithm, a fast API, and a user-friendly graphical user interface (GUI). This tool enables the easy creation of successful and cost-efficient public road testing campaigns for testing ADAS features.

Battery State of Health

In this project, my role encompassed the systematic data extraction from the database, followed by a meticulous tidying process to enhance its usability. Subsequently, I delved into an exploratory phase to gain deeper insights into the data's intricacies. Leveraging machine learning techniques, I navigated through various models to accurately predict the state of battery health. This iterative process allowed for a comprehensive understanding of the data landscape and facilitated the development of robust predictive models.

Vehicle Fleet Monitoring

My primary responsibility in the project was to extract raw data from the database, then meticulously clean and organize it to ensure its accuracy and consistency. Subsequently, I crafted diverse transformations and aggregations to make the data suitable for visualization and key performance indicator (KPI) calculations. Utilizing R Markdown, I presented these insights in HTML format, enabling stakeholders to grasp and interpret the findings easily. This comprehensive process ensured that our visualizations and KPIs were not only informative but also accessible and visually compelling.

Data Enrichment Tool

In this project, I took the lead in designing and implementing a cutting-edge tool for data enrichment. This tool provides an interface enabling integration of APIs into the workflow. This integration facilitates querying for supplementary metadata, enriching the dataset for more comprehensive analysis in subsequent stages. Through this strategic approach, we ensured that our analysis was bolstered by a wealth of additional information, enhancing the depth and accuracy of our insights.
2014 - 2016

Master's Degree in Mathematical Statistic

Department of Mathematics, Faculty of Science, University of Zagreb - Zagreb, Croatia

2011 - 2014

Bachelor's Degree in Mathematics and Computer Science

Department of Mathematics, Faculty of Science, University of Zagreb - Zagreb, Croatia


R, SQL, Python, Markdown


RStudio Shiny


Data Science


RStudio, Docker, Amazon Web Services (AWS)


Data Validation, MySQL


Statistics, Optimization, Data Cleaning, Data Transformation, Data Visualization, Clustering Algorithms, Data Aggregation, Data Scientist, Evolutionary Algorithms, Machine Learning, Time Series Analysis, User Interface (UI), FastAPI, Vehicle Routing, Traveling Salesman Problem (TSP), Graph Theory, Linear Regression, Clustering, APIs

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.


Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring