Antoine Lucas
R / Shiny Engineer · Scientific Software & Data Products
Pharma · Cosmetics · Biotech · Paris, France
Research Engineer & Data Scientist with 5+ years building production-grade software and data products in pharma, cosmetics, and biotech. R / Shiny delivery, reproducible analysis, stakeholder-facing architecture, and technical ownership from discovery through deployment. Background spans statistical modelling, scientific computing, internal platform tooling, and ML systems, with a strong focus on maintainable delivery: documentation, validation, CI/CD, and handover for teams that need to keep using the product long after the first release.
Experience
Sep 2025 – present
- Managed platform tooling across GitForge, Azure ML, Posit Connect, and Databricks, covering deployments, access governance, and lifecycle management.
- Owned a catalog of 20+ R Shiny applications spanning clinical data visualisation, formulation process automation, and researcher-facing data lifecycle workflows.
- Engineered reproducible MLOps and delivery infrastructure using Docker and Databricks.
- Designed and deployed computer vision models (object segmentation) for cosmetics formulation and regulatory R&D applications.
May – Sep 2025
- Led internal upskilling training on Bayesian statistics with R for internal consultants.
- Developed reusable internal R packages and Quarto automated reporting templates.
- Contributed to internal data science projects by quickly adapting to the current team processes and tools, including Shiny app development, Python modules tooling, and data analysis.
- Fine-tuned Microsoft Phi-3-mini-4k-instruct (3.8B) using LoRA (PEFT) on the climatecheck dataset for claim verification, from data preparation to evaluation.
Dec 2024 – May 2025
- Delivered end-to-end pipelines in R and Python for tabular and large-scale omics data, including genomics, transcriptomics, and metabolomics.
- Embedded as the sole data scientist in a fast-paced 8-person startup team building a SaaS product with a FastAPI backend and Vue.js front-end.
- Participated in scientific discussions with agri-food partners, including experimental design, data analysis, and ML approaches for multi-omics integration.
Jul 2023 – Nov 2024
- Owned end-to-end delivery as sole R Shiny developer and Scrum Master, managing backlog, sprint ceremonies, and stakeholder alignment across researchers, managers, and project leads.
- Built R and Python applications to predict and simulate manufacturing plant resource capacity across global sites, driving drug production planning and decision-making from requirements through deployment.
Nov 2021 – Jul 2023
- Supported a senior statistician on exposome and clinical datasets, including biophysical, omics, and microbiome data.
- Characterised clinical phenotypes with multi-block, integrative, multivariate, and variable-selection approaches.
- Contributed to data-visualisation work, including Bayesian-network and other graphical approaches, while proposing suitable statistical methods.
- Defined analysis methodologies for proof-of-concept clinical studies; wrote statistical analysis plans, supported blind-review meetings, programmed analyses in R, and delivered reports for more than 100 clinical studies.
Earlier experience
Feb 2021 – Aug 2021
Modelled hair customer data for personalised recommendations, combining literature review, data management, statistical analyses, machine learning, and communication to Research & Innovation teams.
Feb 2020 – Aug 2020
Performed data management and non-parametric statistical analyses for gut-microbiome clinical studies, then prepared and presented results to biotechnology research teams.
Sep 2019 – Jan 2020
Supported digital-health and wearables studies in R through questionnaire design, workshop preparation, statistical evaluation, and presentation of results to researchers.
Education
2021
2021
Technical Skills
Certifications
GitHub Foundations — GitHub (2024)
Scrum Master — Agilbee (2023)
Languages
French (native)
English (fluent, professional)