Xpressbees - Operations Research Scientist

The Research Scientist will be part of our solution strategies for a wide range of problems including capacity constrained, vehicle routing problems with time windows for deliveries and pickups, dynamic rerouting to cope with disruptions, and scheduling and routing of line haul trucks across the transportation network, topology decision making for network expansion, optimal allocation of volumes between multiple carrier channels, customer demand forecasting, prediction of number of units in a package, forecasting of unit volume requirements etc. Individual with a recognized background in mathematical optimization, including numerical solution of continuous and discrete problems using exact, approximation algorithms, and heuristic methods. The person should have current or prior academic experience with a heavy practical consultative component, or industry experience conducting research in the area of mathematical/statistical modelling and analysis. The candidate must have relevant domain knowledge to critique models and approaches taken by the group in terms of business relevance, technical validity, software architecture, and computational performance. The candidate must have the skills to write documents that influence important decisions by clearly articulating the strategy, business impact, and technical challenges.

Expectations :

- M.S. in Operations Research, Statistics, Applied Mathematics, Computer Science or a related field.

- MBA in OR, or in operations can be considered also.

- Black belt certified in six sigma and have worked on six sigma projects in the past would be preferred but not must.

- 8 to 12 years of experience designing and implementing transportation optimization models with focus on volume and route planning and re-planning; labour and facilities planning. Excellent communication skills, both written and oral with both technical and business people. Ability to speak at a level appropriate for the audience.

- Working knowledge of smooth and non-smooth optimization methods accompanied by associated expertise in the use of tools and the latest technology (e.g. CPLEX, Gurobi, XPRESS).

- A working knowledge of exact, approximation algorithms, and heuristic methods for solving difficult optimization problems like vehicle routing and network design problems.

- The ability to implement models and tools through the use of high-level modelling languages (e.g. AMPL, Mosel, R, Matlab

- Design long term strategies for process design

- Building and Developing a strong team: Significant experience leading teams, developing your directs to consistently deliver valuable projects and performance on core metrics.

- Experience prototyping and developing software in traditional programming languages (C++, Java, Clojure, Python).

- Structurally Identify opportunities to improve on the speed of quality of resolution

- Capable to design end-to-end support process framework taking into consideration

- Experience prototyping and developing software in traditional programming languages (C++, Java, Clojure, Python).

- Familiarity with SQL and experience with very large-scale data. The ability to manipulate data by writing scripts (Perl, Ruby, Groovy), Google OR tool, Arena, SAS, SPSS is preferred

- Statistical analysis, machine learning and data-modeling in a database environment a plus

- Exhibits excellent judgment

- Has relentlessly high standards

- Thinks strategically, but stays on top of tactical execution

- Expects and requires innovation of her/his team