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Resume

Resume

Hi, I'm Armand 👋

I'm a French engineer, data specialist, and entrepreneur based in Île-de-France. Over the last decade, I've moved from writing my first lines of PHP as a teenager to founding a health-data startup, co-authoring a Nature Medicine paper, and helping French hospitals turn their data into something they can actually trust.

This page is the long-form version of my CV — a narrative of how I got here, what I've built, and where I'm headed.

Resume - Armand LEOPOLD
Resume - Armand LEOPOLD.pdf
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The Short Version

  • 🎓 M.Eng. in Computer Science / Big Data — ESIGELEC (2017), top of class in CS (8/304).
  • 💼 8+ years of experience across banking, defense, healthcare, and industry.
  • 🏥 Ex-Institut Curie — Data Engineer → DevOps Engineer → Head of Data Factory.
  • 🛡 Ex-Thales — Data Scientist on defense & intelligence projects.
  • 📄 Published in Nature Medicine (2nd author, federated learning in oncology, 2023).
  • 🚀 Founder & CEO of QALITA — a Data Quality platform for the healthcare sector.
  • 🧠 Today: CTO-as-a-Service through LPD Consulting — Data, AI & Governance expert.

The Early Years: Learning by Building (2009 – 2014)

Long before I had a degree, I had an FTP client and too much free time. Between 2009 and 2014, I taught myself web development by building small personal sites — starting on free.fr pages, then graduating to OVH hosting. HTML, CSS, PHP, MySQL, a bit of Ajax, a lot of trial and error.

That autodidact phase shaped how I still work today: learn by shipping something.

I later formalized this during my engineering school years at ESIGELEC, where I spent two years (2014–2016) as a freelance Junior Full Stack developer — notably rebuilding my school's student website into a responsive, modern platform. Traffic grew by several thousand percent, and three-quarters of the student body ended up subscribing.

In parallel, I took on leadership responsibilities as President of Junior Études ESIGELEC (2015–2016), restructuring the school's junior enterprise: managing a 6-person team, rebalancing its finances, redesigning its processes, and applying to the national Junior Enterprise movement.

Takeaway from this period: I love building things, and I love making teams and systems work better.

Academic Foundations & a Summer in Chicago (2012 – 2017)

  • 2012 — Baccalauréat STI Électrotechnique, with high honors.
  • 2012–2014 — PCSI/MPSI preparatory classes at ESIGELEC, graduating top of my class in Computer Science (1/120).
  • 2014–2017 — Master of Engineering at ESIGELEC, specializing in Big Data and Digital Transformation (BDTN).

In the summer of 2016, I flew to Chicago for a three-month research internship at the Illinois Institute of Technology (BigDataX Lab), working on a Big Data architecture for wearable devices. That experience confirmed two things: I loved research-grade problems, and I loved building systems that move large volumes of data reliably.

First Professional Role: Crédit Agricole (2016 – 2017)

My first "real" job was as a Junior Data Analyst at Crédit Agricole in Rouen, under a work-study contract. I built scoring models and CRM analytics using SAS, R, Python, and SQL.

The highlight: a secondment to the Crédit Agricole DataLab in Montrouge, where I collaborated with AI researchers on a consumer panel dataset and presented my findings back to my local management.

It was my first taste of enterprise data science — and my first reminder that the hardest part isn't the model, it's making the insights land with the business.

Thales: Defense, Aerospace & NLP (2017 – 2019)

I joined Thales straight out of engineering school on a permanent contract.

Junior Data Scientist — Toulouse (Nov 2017 → Apr 2018)

Based in Labège, I worked on two fronts:

  • Predictive maintenance on flight data for a Portuguese A320 fleet.
  • Flight-plan ingestion and Kibana dashboards for the DSNA DTI (the French government entity managing air traffic).

I also contributed to technical writing on RFPs and gave internal talks on emerging topics like blockchain.

Data Scientist — Paris / Vélizy (Apr 2018 → Feb 2019)

I moved to a more sensitive domain: OSINT and intelligence. I built social graph analyses from open-source data for French intelligence services, applied NLP and sentiment analysis at scale, and contributed to a large data platform project for the French Army.

Stack: Scala, Spark, Hadoop, JanusGraph, PageRank, Linkurious, PyTorch, TensorFlow, CDAP, Java.

Institut Curie: Four Years at the Heart of Healthcare Data (2019 – 2023)

Joining the Institut Curie — one of Europe's leading oncology research institutes — was the turning point of my career. I spent four years there across three roles.

1. Data Engineer (Apr 2019 → Aug 2020)

I was assigned to the HealthChain consortium — a national R&D project combining Institut Curie, Centre Léon Bérard, AP-HP, Owkin, and others to build a federated machine learning infrastructure on blockchain, capable of training models on multi-centric health data without centralizing it.

Concretely, I:

  • Built Institut Curie's clinical and imaging dataset for triple-negative breast cancer cohorts.
  • Processed whole-slide histopathology images (BigTIFF), leveraged DICOM metadata for pseudonymization.
  • Harmonized data schemas between Curie and Centre Léon Bérard.
  • Operated Curie's node on Owkin's Substra federated learning platform.
  • Designed and built HDM (Health Data Metrics) — an internal tool for health data quality profiling. HDM is the conceptual and technical ancestor of what would later become QALITA.

This work culminated in a co-authored paper (2nd author):

Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer
Nature Medicine, January 2023 — DOI: 10.1038/s41591-022-02155-w

2. DevOps Engineer (Sep 2020 → Sep 2022)

The Data Factory was growing fast, and our deployment practices needed to grow with it. I took ownership of the infrastructure and DevOps layer:

  • Defined the Kubernetes namespace urbanization strategy.
  • Built a full GitLab CI/CD pipeline, deployed Sonatype Nexus as our internal package registry (Docker images, Helm charts), and integrated HashiCorp Vault for secrets.
  • Rolled out observability with Kibana (ELK), GitLab Monitor, and Statuspage.
  • Wrote extensive internal documentation and evangelized DevOps practices to scientific profiles.
  • Gave a public talk — "DevOps at the service of health data at Institut Curie" — to 101 attendees in November 2021.

We moved the Data Factory from artisanal to industrial — a reproducible, observable, auditable chain.

3. Head of Data Factory (Oct 2022 → Apr 2023)

Promoted to lead the Data Factory, I managed a team of 5 Data Engineers and Data Scientists, ran the portfolio of scientific and industrial projects (collaborations with AP-HP, Owkin, Arkhn, UNICANCER, Health Data Hub), and, most importantly, led the technical groundwork for Institut Curie's Health Data Warehouse (EDS).

I organized and animated three working groups (Security & Infrastructure, Data Governance, Business & Research) across 14 sessions, aligning our architecture with the CNIL EDS reference framework (chapter 10 – security).

At the end of this chapter, I made the hardest professional decision of my career: leave to start my own company. I'd seen firsthand that data quality in health data warehouses was a massive, under-invested problem — and I wanted to solve it properly.

QALITA: Founding a Health-Data Startup (Apr 2023 → Apr 2026)

I founded QALITA in April 2023, after 1.5 years of maturation and early discussions with Institut Curie. The mission: help organizations — especially hospitals — measure, monitor and manage the quality of their data.

I lived the full startup lifecycle, in five distinct phases.

Phase 1 — Foundation & MVP (Apr 2023 → Feb 2024)

  • Created the company, wrote the business plan, negotiated and signed a €40K mandate with Institut Curie (project UNIBASE, a quality audit on ConSoRe cohort data).
  • Built the first MVP of the QALITA Platform solo: Python/FastAPI backend, React/Next.js frontend, PostgreSQL, a Python profiling worker, a CLI, and Helm charts.
  • Deployed on Curie's Kubernetes infrastructure, produced the quality audit report for UNIBASE.
  • Key lesson: a technical prototype, however well-built, doesn't become an adopted product without an active client sponsor and a prioritized use case.

Phase 2 — Freelance at Axens to self-fund (Feb 2024 → Aug 2024)

To keep QALITA alive, I took a 7-month freelance mission at Axens, building custom Grafana plugins for their "Connect'In" production-monitoring platform. My first hands-on experience with Azure DevOps.

In parallel:

  • Hired and managed a marketing freelance for 3 months (Lemlist setup, copywriting, LinkedIn overhaul).
  • Ran a commercial demo at the Institut Paoli-Calmette with their CIO.
  • Partnered with a senior advisor (20+ years in Pharma).
  • Completed the Bpifrance Growth Diagnostic, which triggered a major strategic pivot from R&D to GTM.

Phase 3 — Go-to-Market #1 (Sep 2024 → Mar 2025)

The first real GTM push:

  • ~10 Lemlist/email campaigns, **~2,500 contacts approached**, multi-step funnels.
  • Three trade shows: AI for Health (Station F) — where I gave my first English-language talk, "AI Models: Why Data Quality Matters" — CHU Healthtech Connexion Day (Lille), and Tech4Health.
  • Strategic win: referenced on the UniHA / LogiMed public-procurement central in March 2025 — a major credibility asset for selling to French public hospitals.
  • First real commercial conversion at AI for Health: a direct contact led to a POC agreement with CHU d'Angers in December 2024.
  • Hard truth learned: the CHU/CLCC market wasn't mature enough for cold outbound. Human contact — trade shows, pitches, network — is the only real conversion engine in French public health.

Phase 4 — R&D and First Hospital Deployment (Apr 2025 → Sep 2025)

Armed with a €116K Innovation Loan from Bpifrance (dossier built solo), I went deep on product:

  • Extended QALITA from flat-file scanning to multi-level database scanning — a full refactor of backend, frontend, profiling packs, jobs, CLI, and worker.
  • Built QALITA Studio, an agentic AI layer inside the platform: a conversational agent using tools to diagnose data quality issues autonomously, auto-enrich metadata with GenAI, and assist in code generation for quality packs.
  • Deployed in production on CHU d'Angers' eHOP Health Data Warehouse in September 2025. Trained ~10 internal users across Pharmacology, Data Science, and biostatistics.

Phase 5 — Go-to-Market #2 (Oct 2025 → Apr 2026)

A second, more structured GTM push with a proper team: a junior sales intern, a senior marketing freelance, and a graphic designer.

  • Three trade shows as an exhibitor in late 2025.
  • 🏆 Won the "AI, Data & Interoperability" Pitch Prize at the CHU Connexion Day in Bordeaux (December 2025).
  • Second CHU deployment secured: CHU de Montpellier — one of France's oldest health data warehouses — currently in purchasing via UniHA / LogiMed.
  • Opened the door to EDGAR / RESPIC — a France 2030-winning consortium of 10 ESPIC hospitals, 3.2M patients, OMOP-CDM interoperability standard — where QALITA is positioned as the data-quality brick.
  • Managed startup runway tightly, with transparent communication to Bpifrance.

Running QALITA taught me entrepreneurship the hard way: product, sales, fundraising, hiring, cash management, and picking yourself up after slow deals — all at once.

Today: CTO as a Service via LPD Consulting

In parallel with QALITA's GTM #2, I launched LPD Consulting to offer what 10+ years in the field have taught me — directly to organizations that need it.

What I do

  • CTO / CDO / Lead Data Architect missions.
  • Expert consulting on Data Quality, Data Governance, and AI/LLM projects.
  • Hands-on Data Engineering & MLOps when needed.

Where I add the most value

  • Healthcare / HealthTech (EDS, CHU, CLCC, Pharma, ESPIC).
  • Regulated environments (CNIL EDS framework, RGPD, health data).
  • Data-quality-driven AI projects (the cleaner your data, the better your models — I've literally built a company on that premise).
  • Teams transitioning from artisanal to industrial data practices (CI/CD, Kubernetes, observability, governance).

Side Projects

Some things I build on evenings and weekends:

  • Previly (Nov 2025 → present) — a personal-finance SaaS I'm building from scratch: bank-statement OCR, Powens sync, intelligent transaction categorization, an agentic AI assistant, accounting module, and wealth-management recommendations. Stack: Next.js, Tailwind, Docker, LangChain.
  • Homelab (2020 → present, v3) — a 4-node Raspberry Pi 5 cluster (16GB RAM, 1TB NVMe, Longhorn storage, OVH backup, UPS), running Rancher, Grafana, Loki, Pi-hole, and more.
  • Krypto — algorithmic crypto trading.
  • ScrapYourFlat — real-estate aggregator powered by web scraping.
  • Twitter Social Project — Big Data analysis on social networks.

Technical Toolbox

Languages & Data Science: Python, R, SAS, Scala, Java, TypeScript, SQL · Scikit-Learn, Pandas, PyTorch, TensorFlow · MLflow, MLOps, LangChain, NLP

Web & Product: React, Next.js, Node.js, FastAPI, Tailwind, Figma, Webflow

Data Engineering: Spark, Airflow, Kafka, Hadoop, Hive, HBase, JanusGraph · PostgreSQL, MySQL, Elasticsearch, Redis, Cassandra

DevSecOps & Cloud: Git, GitLab, GitHub, Azure DevOps · Docker, Kubernetes, Helm · Terraform, Vault, ArgoCD · AWS, Azure, GCP, OVH · Grafana, Kibana

Transferable Skills

  • Team management (up to 5 people at Institut Curie).
  • Entrepreneurship — product, sales, fundraising, cash management.
  • Scientific publication (Nature Medicine).
  • Data governance in regulated environments (CNIL EDS).
  • Technical architecture for data platforms.
  • Public speaking (101-attendee conference, international talks in English, award-winning pitches).
  • Fluent English (TOEIC 955).

Industries I know well

Healthcare & HealthTech · Banking · Defense, Intelligence & Aerospace · Industry

Let's talk

I'm currently available for CTO / CDO / Lead Data Architect / Data Quality / Data Governance / AI & LLM consulting missions — full-time or part-time, on-site in Île-de-France or remote.

If you're building something at the intersection of data, AI, and healthcare — or if you just need a seasoned hand to help your data team level up — I'd love to hear from you.