About the Role
We are seeking a Research Scientist or Applied Scientist to lead our team in innovating topology, routing planning, and dispatch solutions for last mile programs using Operations Research, computer vision, Machine Learning, and deep learning techniques.
Key Responsibilities
- Design and develop advanced mathematical optimization models to drive business and technical solutions in areas such as routing planning, supply chain optimization, network optimization, economics, and control theory.
- Apply mathematical optimization and control techniques to design optimal or near-optimal solution methodologies for in-house decision support tools and software.
- Research, prototype, simulate, and experiment with these models using Python or R, and participate in production-level deployment.
- Create, enhance, and maintain technical documentation.
- Present to Scientists, Product, and Software Engineering teams, as well as Stakeholders.
- Lead project plans from a scientific perspective by managing product features, technical risks, milestones, and launch plans.
- Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists.
Requirements
- PhD or Master's degree with 4+ years of quantitative field research experience, or 3+ years of applying optimization and machine learning for solving real-world problems in industry.
- Proficiency in C/C++, Java, or Python, and at least one optimization library (CPLEX, XPRESS, or Gurubi), and at least one machine learning or statistical modeling library (R, Matlab, Scikit-learn).
- Preferred qualifications include experience designing and supporting large-scale optimization systems in a production environment, working with large data sets, big data, and analytics, and specialization in transportation problems.
Location
We are open to hiring candidates to work out of one of the following locations:
Tokyo, Japan
Salary
The salary information can be provided individually prior to the first interview.
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