Data Scientist - Optimization
Location
Toulouse (Hybrid)
About Alteia
Alteia is a leading enterprise AI software company that empowers organizations to accelerate their digital transformation by harnessing the power of visual intelligence. Our cutting-edge platform enables customers across various industries (such as Energy, Grid Infrastructure, Environment, Manufacturing, and more) to efficiently manage, analyze, and operationalize vast amounts of visual data (images, videos, Lidar, etc.). By combining computer vision, geospatial analysis, and artificial intelligence, we help businesses build and deploy AI applications at scale, turning complex data into actionable insights and tangible business outcomes. We foster a collaborative, innovative, and fast-paced environment where technical excellence and continuous learning are highly valued.
Job Summary
Alteia is seeking a skilled Data Scientist specialized in Optimization to join our multidisciplinary Engineering team. Working alongside Computer Vision Engineers and Machine Learning Specialists, you will tackle advanced data processing challenges derived from drone and satellite feeds. In this role, you will be pivotal in formulating and solving complex constraint-based problems to optimize operations, maintenance, and resource allocation for critical infrastructures.
Key Responsibilities
- Operational Optimization: Formulate and solve constraint-based optimization problems for infrastructure planning and piloting. This includes modeling optimal resource allocation (teams, technical assets, budgets) while respecting complex operational constraints.
- Scheduling & Maintenance: Develop optimal maintenance plans to efficiently sequence and coordinate field teams, taking into account availability, prioritization, and business-specific rules.
- Routing & Planning: Solve complex planning and routing challenges, including Traveling Salesman Problem (TSP) variants and Vehicle Routing Problems (VRP).
- Algorithm Implementation: Implement combinatorial and continuous optimization methods to deliver robust, operationally viable solutions.
- Machine Learning Integration: Design and implement ML and Deep Learning models adapted to industrial constraints, collaborating closely with CV/ML engineers to deploy solutions into production pipelines.
- Innovation: Participate in technology watch, proposing innovative approaches and evaluating their feasibility at the frontier of research and industrial application.
Required Qualifications & Skills
- Education & experience : Master’s degree (M2 or equivalent) in Computer Science, Applied Mathematics, Data Science, or a related field. 2 to 3 years of professional experience in Data Science, Machine Learning, or Optimization.
- Operations Research: Strong command of constraint optimization concepts, combinatorial optimization, and OR problems (TSP, VRP, resource allocation). Proficiency with optimization tools/libraries is highly appreciated (e.g., OR-Tools, Pyomo, CVXPY ).
- Machine Learning: Good understanding of Machine Learning and Deep Learning models. Experience with PyTorch (or equivalent), including cloud/distributed environments, is a strong plus.
- Python Proficiency: Excellent mastery of Python and its scientific ecosystem (NumPy, Pandas, SciPy, Scikit-learn).
- System & Version Control: Comfort with Linux/Unix environments and daily use of Git.
- Geospatial Data: Knowledge of GIS concepts and tools (GDAL, QGIS, GeoPandas, Rasterio) is a definite asset.
- Language: Professional proficiency in English and French (written and oral).
- Soft Skills: Rigorous analytical mindset, ability to model complex problems, autonomy, curiosity, and a strong team spirit.