面議（經常性薪資達4萬元或以上） 新北市土城區 3年工作經驗 1天前更新
＜About the Job＞
As an Optimization Data Scientist, you will play a key role in driving Optimization and Operations Research initiatives across critical business functions, including supply chain, production planning and scheduling, capacity allocation, inventory and logistics, industrial engineering, and financial performance. Leveraging advanced mathematical modeling and algorithm design, you will transform complex data into actionable insights, enabling smarter decisions and unlocking optimization-driven business value.
＜Job Responsibilities＞
．Design, implement and refine advanced Mathematical Programming / Operations Research / Meta-heuristics / Numerical Simulation / Optimization Algorithm Models (at least one of the fields).
．Ensure alignment of optimization initiatives with the requirement goal defined by key stakeholders and company objectives and identify new formulations or decomposition strategies for model improvements.
．Executing large-scale optimization projects, including problem formulation, constraint engineering, model building, algorithm development, solver tuning, and deployment, etc.
．Works closely with a team of project manager, data scientist, business data analyst, data engineer, supply chain / IE / PMC domain expert, etc.
．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others.
．Self-motivated, Result-oriented, and interested in applying quantitative & optimization methods to solving real-world supply chain, manufacturing, and engineering problems.
＜Skills＞
．Experience with any one of Mixed Integer Programming (MILP), Linear Programming (LP), Non-linear Programming (NLP), Constraint Programming (CP), Meta-heuristics (GA / SA / Tabu Search / ALNS…), Stochastic / Robust Optimization, Numerical Simulation…, etc., model/algorithm building of the practical application in the industry.
．Hands-on experience with commercial or open-source solvers such as Gurobi, Cplex, OR-Tools, or SCIP.
．Familiarity with programming languages like Python or C++ or Java.
．Advanced ability to perform problem decomposition, constraint analysis, and working knowledge of operations research theory.
．Ability to visualize optimization results, KPI trade-offs, and solver behavior (e.g., gap convergence, IIS diagnostics) in the most effective way possible for a given task, especially debug and troubleshoot infeasible / unbounded models.
＜Minimum Qualifications＞：
．2+ years of professional experience with a degree of Ph.D. / Ph.D. Candidate, or 3+ years of relevant working experience with a degree of Master.
．Major in Industrial Engineering / Operations Research / Computer Science / Information Engineering / Information Management / Applied Mathematics / Supply Chain Management or related quantitative discipline (such as in a field where there is intensive training in quantitative & optimization methods, e.g., Operations Research, Industrial Engineering, Management Science, Transportation, Logistics, Statistics, Economics, Electrical and Computer Engineering, Physics).
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