
About this role
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Design and implement optimization and ML models to solve business problems
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Train, evaluate, and continuously improve models using production feedback
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Deploy models as scalable services or pipelines
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Collaborate with backend teams to integrate models into core systems
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Ensure solutions are robust, explainable, and maintainable
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Define and monitor model performance and business impact metrics
Requirements
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3+ years of hands-on experience in data science, applied machine learning, or optimization
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Strong background in mathematical modeling, optimization, or operations research
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Experience with linear, integer, and mixed-integer programming
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Knowledge of constraint-based optimization and heuristics/meta heuristics
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Proven experience training, validating, and tuning models
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Proficient in Python for data science and modeling
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Hands-on experience with libraries such as NumPy, Pandas, SciPy, and OR tools (Pyomo, OR-Tools, PuLP, Gurobi, CPLEX)
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Familiarity with ML frameworks (scikit-learn, PyTorch, TensorFlow)
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Ability to translate business problems into mathematical or statistical models
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Experience deploying models to production (APIs, batch jobs, pipelines)
Benefits
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Social insurance
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Medical insurance
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Transportation allowance
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Hybrid Work Environment