Senior Data Scientist and Optimization Engineer

• Master mathematical modeling techniques (LP, MILP, CP, NLP would be a plus) to translate business needs in the form of variables, constraints, objective function with a posture which aims to support the business in the phase of ideation.
• Master modeling environments, in particular Pyomo and/or OR-Tools.
• Know open-source/commercial solvers (Gurobi, CPLEX, Coin-OR, etc.). Knowledge of advanced resolution techniques (column generation, Dantzig-Wolfe, Lagrangian Decomposition, etc. is a plus).
• Master Data Exploration techniques to collect, clean and prepare data with a posture that aims to support the profession in the ideation phase.

• Know how to perform exploratory and descriptive analyses of input data, using statistics and visualizations, to identify trends, correlations, anomalies, opportunities for optimization or value creation. Design, develop, test and deploy Data science and Optimization models adapted to business issues, using various approaches (Optimization, Machine Learning, Computer Vision, Generative AI, etc.).
• Respect good industrialization practices (versioning, monitoring, CI/CD, etc.) to ensure the quality, reliability and security of solutions in production.
• Document and present the results of analyses and models to internal stakeholders using appropriate supports (reports, dashboards, etc.).

• Participate in the design/maintenance of new tools/packages common to the organization.
• Challenge the team's vision.
• Participate in CoPs (Communities of Practice) and team rituals.

• Must have: mastery of statistical and mathematical tools, mastery of programming languages (Python preferably) and underlying data processing libraries, ability to collect, clean and analyse structured or unstructured data, understanding of the main data processing algorithms machine learning and their applications.
• Nice to have: familiarity with data science frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, Keras, etc., experience in visualizing and communicating results, knowledge of advanced AI methods such as deep learning , NLP or computer vision

• Must have: Master mathematical modeling techniques at least linear (LP, MILP). Master modeling environments, notably Pyomo and/or OR-Tools. Know open-source/commercial solvers (Gurobi, CPLEX, Coin-OR, etc.).
• Nice to have familiarity with advanced solution techniques (column generation, Dantzig-Wolfe, Lagrangian Decomposition, etc.). Knowledge of Constraint Programming and Non-linear Programming.

• Must have good command of git and first experience in a DevOps context (CI/CD, with github or similar), an appetite for software craftmanship / clean code, environment (squad, CoP, coaches) helps to spread.
• Nice to have: knowledge of micro-services, experience in AWS/Azure cloud technologies, experience in hexagonal Architecture.

NES Fircroft