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Design and implement optimization and ML models to solve business problems
Train, evaluate, and continuously improve models using production feedback
Deploy models as scalable services or pipelines
Collaborate with backend teams to integrate models into core systems
Ensure solutions are robust, explainable, and maintainable
Define and monitor model performance and business impact metrics
3+ years of hands-on experience in data science, applied machine learning, or optimization
Strong background in mathematical modeling, optimization, or operations research
Experience with linear, integer, and mixed-integer programming
Knowledge of constraint-based optimization and heuristics/meta heuristics
Proven experience training, validating, and tuning models
Proficient in Python for data science and modeling
Hands-on experience with libraries such as NumPy, Pandas, SciPy, and OR tools (Pyomo, OR-Tools, PuLP, Gurobi, CPLEX)
Familiarity with ML frameworks (scikit-learn, PyTorch, TensorFlow)
Ability to translate business problems into mathematical or statistical models
Experience deploying models to production (APIs, batch jobs, pipelines)
Social insurance
Medical insurance
Transportation allowance
Hybrid Work Environment
You'll no longer be considered for this role and your application will be removed from the employer's inbox.