AI Applications & Data Science Consultant
You will join a leading integral R&D; environment where advanced AI-driven applications support researchers in their daily work—from data analysis and statistical modelling to predictive insights and dashboarding.
These applications, built mainly with Shiny (R) and Streamlit (Python) , are part of a growing analytics ecosystem running on a dedicated internal platform. The mission combines maintenance of existing AI/statistical tools and development of new data-driven applications based on real user needs.
You will act as a bridge between business users (researchers) and technical teams , ensuring applications remain reliable, scalable, and relevant.
What you will do
- Investigate and fix issues in AI algorithms (bugs, performance, data pipeline failures)
- Maintain and improve existing Shiny (R) and Streamlit (Python) applications
- Ensure stability after platform or dependency updates
- Develop new interactive modules (dashboards, analytics tools, reporting apps)
- Analyse business needs and translate them into technical solutions




- Optimize and refactor Python and R codebases
- Manage data pipelines and connectors (APIs, databases, files)
- Conduct testing (UAT, unit tests, integration tests)
- Collaborate with data scientists, statisticians, and business users
- Document all developments and processes (French & English)

Qualifications
What we are looking for
Required
- 3–5 years of experience in Python and/or R development
- Experience with Shiny (R) and/or Streamlit (Python)
- Strong debugging and problem‑solving skills
- Experience maintaining production‑level applications
- Solid knowledge of:
- Data manipulation (Pandas / dplyr)
- Data visualisation (ggplot2, plotly, matplotlib, altair)
- Experience with Git/GitHub (PRs, branching, versioning)
- Understanding of basic AI/ML concepts (evaluation metrics, overfitting, pipelines)
- Ability to work in a bilingual environment (French & English)

Nice to have
- Experience wit

📌 AI Applications (España)
🏢 Talan Group
📍 España