About
Roland Macheboeuf — data, machine learning & software craftsmanship
Centrale Lille engineer with over 4 years shipping to production — from a maritime insurance SaaS built single-handedly to profitability, to a tech lead role at TotalEnergies. Data engineering, machine learning and software craftsmanship, with one constant: understanding the business need and delivering code that stands the test of time.
Experience
OCTO Technology (Accenture)— Paris
Data Consultant · Mar 2024 – Apr 2026
TotalEnergies
Data Proxy Tech Lead · Apr 2025 – Dec 2025
Building data products in production on Databricks/AWS (Data Mesh approach) for renewable asset portfolio optimisation.
- Significant reduction in Spark processing costs through workload optimisation and FinOps monitoring.
- Hexagonal architecture, automated testing and proactive monitoring (dashboards, alerting, post-mortems) to make production more reliable.
- Shared repositories (inner-sourcing), including a UI tool running in production, to unify practices across teams.
- Mentoring junior engineers (code reviews, clean code).
IPSEN
Data Architect · Jan 2025 – Mar 2025
Defining the target Data Mesh architecture and master data management (MDM) for a global data platform, in a regulated pharmaceutical environment.
- Evaluated several platforms (Databricks, Snowflake, Microsoft Fabric) to balance cost, governance and scalability.
- Target state enabling data products interoperable across business domains, in both batch and streaming.
Streem Group
Data Engineer · May 2024 – Dec 2024
Designed a hybrid on-premise/Azure architecture for new analytics capabilities.
- Developed data pipelines (DBT, Airflow) combining on-premise and cloud data.
- Industrialised orchestration and a purpose-built testing framework for DBT, strengthening reliability and production standards.
UK Government
ML Researcher · Apr 2024
Audited video deepfake detection models during a government hackathon.
- State-of-the-art analysis (deepfake generation and detection).
- ML/MLOps recommendations to strengthen the existing accelerators.
Trapil (via MP Data)— Paris
Computer Vision ML Engineer · Sep 2023 – Mar 2024
Designed and trained computer vision models (PyTorch) to analyse ultrasonic images of hydrocarbon pipelines.
- Detection, localisation and classification of defects under tight compute-time constraints, with high recall on critical defects.
- Edge deployment of a multi-threaded orchestrator and a Python API integrated into the existing software.
Meetrisk— Paris
ML Engineer & Full Stack Developer · Mar 2022 – Aug 2023
Working in tandem with the CEO, an insurance expert, I built from scratch a maritime risk-rating SaaS platform — profitable in under 18 months.
- Led customer discovery and technical scoping: translating underwriters' expertise and weak signals into ML risk models.
- Reduced exposure to vessels later involved in serious incidents.
- Designed and scaled on Kubernetes (Python/React): real-time ingestion of vessel positions, batch ML processing.
WeSmart— Brussels
ML Engineer · Apr 2019 – Jul 2019
Developed and put into production (API) an energy-consumption predictor.
- Forecasting model on IoT time-series data.
- Deployed via an API (Python, scikit-learn, Docker).
Amadeus SAS— Nice
ML Researcher · May 2018 – Aug 2018
Prototyped deep learning models (Python/Keras) to fill in missing strategic data for B2B users.
- Automatic generation of hotel descriptions (LSTM).
- Ranking images by attractiveness (CNN, transfer learning).
Education
Centrale Lille & Master's degree in mathematics — University of Lille
Sep 2016 – Jul 2019 · Lille
Data science specialisation: machine learning, Bayesian statistics, optimisation, signal processing.
Advanced coursework from the Master's in mathematics (Centrale Lille – University of Lille partnership): functional analysis, stochastic calculus, statistics.
Final-year dissertation: applying machine learning to finance.
Group project (project lead): dynamic carpooling platform, optimisation with metaheuristics (Java, multi-threading).
Preparatory classes for engineering schools (CPGE) — physics and chemistry
Sep 2014 – Jun 2016 · Lille
Two years of intensive preparation for the entrance exams of the French engineering grandes écoles (mathematics, physics, chemistry).
Conservatoire de Lille
Sep 2019 – May 2022 · Lille
Advanced training in piano and music theory (CEPI/CPES): performance, writing, sight-reading, chamber music.
Cycle 3 certificate awarded in May 2022.
Certifications
AWS Certified Solutions Architect – Professional
Amazon Web Services · In progress (2026)
Databricks Certified Data Engineer Professional
Databricks · Obtained May 2024 — expired May 2026
Databricks Certified Machine Learning Professional
Databricks · Obtained May 2024 — expired May 2026
Machine Learning Engineering for Production (MLOps) Specialization
Coursera (DeepLearning.AI) · Obtained May 2023
Deep Learning Specialization
Coursera (DeepLearning.AI) · Obtained February 2022
Expertise
Before writing a single line of code, I seek to understand the actual need: I ask a lot of questions, scope the problem, then propose a solution that fits it — rather than chasing the latest trend.
Languages
- French
- Native
- English
- Fluent — C1 (TOEIC 985/990)
- Korean
- Pre-intermediate