Job Description –
looking for an Applied Scientist with background in Operations Research, Optimization, Supply Chain and/or Simulation to support science efforts to integrate across inventory management functionalities. Our team is responsible for science models (both deterministic and stochastic). We formulate and solve challenging large-scale optimization problems which ingest demand forecasts and produce optimal procurement, production, distribution, and inventory management plans. In addition, we also work closely with the demand forecasting, material procurement, production planning, finance, and logistics teams for our customers to co-optimize the inventory management and supply chain with given operational constraints.
Responsibilities include:
- Design and develop advanced mathematical, simulation, and optimization models and apply them to define strategic and tactical needs and drive appropriate business and technical solutions in the areas of inventory management and distribution, network flow, supply chain optimization, and demand planning
- Apply mathematical optimization techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software
- Research, prototype and experiment with these models by using modeling languages such as Python; participate in the production level deployment
- Create, enhance, and maintain technical documentation, and present to other Scientists, Product, and Engineering teams
- Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans
- Influence the organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Expertise in optimization: linear, non-linear, mixed-integer, large-scale, network, robust, stochastic
- Experience in building optimization models and implementing them on OR tools (e.g. CPLEX, Gurobi, XPRESS)
- Expertise in validating and simulating math optimization model
- Experience designing and supporting large-scale optimization systems in a production environment
Any graduate