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