数据科学家
Data Scientist
我们寻找一名数据科学家，负责设计和开发优化和机器学习模型，用于在竞争性项目之间分配稀缺的零部件和资源。你将构建涵盖混合整数规划、约束优化和机器学习驱动预测的算法，将硬性供应限制转化为可辩护、可审计的分配决策。你将负责整个建模生命周期，从问题定义和数据探索到验证和生产部署，与项目相关方紧密合作，将竞争性优先事项转化为可解决的目标。这是一个高可见度的职位，适合能够自如地在严谨的定量建模和务实的项目沟通之间切换的人选。
关键职责：
- 为在竞争性项目之间分配稀缺零部件和资源设计并实现优化模型（例如混合整数线性规划、约束规划）。
- 开发机器学习模型用于预测需求、供应风险和零部件可用性，并将这些预测直接整合到分配逻辑中。
- 将模糊的、竞争性的项目优先事项转化为正式的目标函数和约束条件。
- 验证模型输出是否符合历史分配决策和相关方的期望；随着新约束的出现不断迭代模型结构。
- 构建并维护数据管道，确保优化模型能及时获取实时库存、需求和项目数据。
- 向非技术的项目和供应链相关方展示建模的权衡和建议。
- 指导初级数据科学家掌握优化技术和建模最佳实践。
- 与软件工程师合作，将模型产品化为可扩展的服务。
- 硕士或博士学历，专业为运筹学、应用数学、计算机科学、工业工程或相关量化领域（或具有同等实践经验）。
- 6年以上构建优化和/或机器学习模型的经验，用于资源分配、调度或供应链问题。
- 深入使用优化求解器（例如 Gurobi、CPLEX、OR-Tools）的经验，以及构建混合整数线性规划/约束优化问题的能力。
- 强大的 Python 技能，熟悉机器学习框架（例如 scikit-learn、PyTorch）和数据处理库（pandas、NumPy）。
- 具有处理混乱、现实世界中的供应链、库存或项目数据的经验。
- 优秀的沟通能力；能够向项目相关方清晰表达复杂的权衡关系。
查看英文原文
We're looking for a Data Scientist to lead the design and development of optimization and machine learning models that allocate scarce parts and resources across competing programs. You'll build algorithms spanning mixed-integer programming, constraint optimization, and ML-driven forecasting that turn hard supply constraints into defensible, auditable allocation decisions. You'll own the full modeling lifecycle, from problem formulation and data exploration through validation and production deployment, partnering closely with program stakeholders to translate competing priorities into solvable objectives. This is a high-visibility role for someone who moves fluidly between rigorous quantitative modeling and pragmatic, program-facing communication.
Key Responsibilities:
- Design and implement optimization models (e.g., mixed-integer linear programming, constraint programming) for allocating scarce parts and resources across competing programs.
- Develop ML models to forecast demand, supply risk, and part availability, feeding those forecasts directly into allocation logic.
- Translate ambiguous, competing program priorities into formal objective functions and constraints.
- Validate model outputs against historical allocation decisions and stakeholder expectations; iterate on formulations as new constraints emerge.
- Build and maintain the data pipelines needed to keep optimization models current with live inventory, demand, and program data.
- Present modeling tradeoffs and recommendations to non-technical program and supply-chain stakeholders.
- Mentor junior data scientists on optimization techniques and modeling best practices.
- Partner with software engineers to productionize models as scalable services.
- Master's or PhD in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering, or a related quantitative field (or equivalent practical experience).
- 6+ years of experience building optimization and/or ML models for resource allocation, scheduling, or supply chain problems.
- Deep hands-on experience with optimization solvers (e.g., Gurobi, CPLEX, OR-Tools) and formulating MILP/constraint optimization problems.
- Strong Python skills, with experience in ML frameworks (e.g., scikit-learn, PyTorch) and data manipulation libraries (pandas, NumPy).
- Experience working with messy, real-world supply chain, inventory, or program data.
- Excellent communication skills; comfortable presenting complex tradeoffs to program and business stakeholders.
Preferred Qualifications:
- Experience with allocation problems in aerospace, defense, or manufacturing supply chains.
- Familiarity with ERP systems (e.g., SAP) and how allocation decisions flow into procurement and production planning.
- Experience deploying optimization models as production services (APIs, batch pipelines).
- Exposure to reinforcement learning or Bayesian methods for decision-making under uncertainty.
We Value:
- Drive: Passion and energy to implement quality technical solutions. Self-motivation and intellectual curiosity
- Commitment to Quality: Passion to conceive and produce world-class solutions that drive real-world value for the customer
- Customer Focus: Consultative approach to solving problems for customers. Expectations management.
- Communication: Superior communication skills. Ability to clearly articulate problems, solutions, risks, rewards etc. (written and verbal)
- Technical Skills: Love for technology. You have to be inherently passionate about technology.
- Business Acumen: Technology ultimately is used to enable the business. We look for people who understand how the businesses can be enabled through their technical solutions
All your information will be kept confidential according to EEO guidelines.
Oteemo is an industry-leading technology consulting firm at the forefront of AI-driven, cloud native, enterprise DevSecOps transformation. We build intelligent, automated, secure systems for organizations tackling their toughest technical and business challenges and we're pushing the boundaries of what AI, generative AI, and agentic systems can do in production, not just in theory. Join us and you'll work alongside recognized experts on cutting-edge projects that blend cloud native architecture, extreme automation, and AI/ML at the core. We foster a dynamic, inclusive, and collaborative culture built on continuous learning, where your ideas shape real outcomes for our clients. If you're passionate about building what's next in AI and cloud technology and want to do it with a team that sets the standard rather than follows it, Oteemo is where you belong.
Originally posted on Himalayas