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hackajob is partnering with Just Eat to fill this position. Create a profile to be automatically considered for this role—and others that match your experience.
As a Senior Operations Research (OR) Scientist, you will play a pivotal role in designing an optimization system that balances the supply/demand capacity of the logistics network. You will dive deep into large-scale geospatial and real-time data to design automated decision-making systems that operate in a dynamic, real-world environment. You will develop high-performance robust optimization models, utilizing techniques like mixed-integer programming (MIP), constraint programming, stochastic programming, metaheuristics, etc. and launch them into production to control operational decisions at scale.
You will collaborate with Data Scientists to create hybrid systems where Machine Learning guides optimization constraints and objective functions. You will help bridge the gap between prediction and control, working with engineers to define the simulation and experimental environments needed to validate these systems. In this senior role, you’ll work closely with fellow scientists to establish and implement best practices, share constructive feedback, and mentor junior team members. Staying at the forefront of OR advancements, you’ll explore new algorithms, architectures, and methodologies to enhance the performance of our products and algorithms.
These are some of the key ingredients to the role:
Advanced proficiency in designing large scale, real-time optimization systems for time critical decisions, with extensive experience applying these techniques in production environments.
Deep expertise in exact optimization techniques (mixed-integer programming/decomposition), robust optimization (Stochastic/Worst case/Scenario based programming) and meta-heuristic methods.
Extensive hands-on experience with commercial solvers (CPLEX/Gurobi) and open-source alternatives (HIGHS/SCIP/Google OR-Tools)
Proficiency in Python object oriented programming, and experience with libraries such as Pyomo, PuLP, or GurobiPy.
Hands-on experience in setting up simulations for model validation and data generation.
Proven experience in getting models to production, scaling, and maintaining them for long-term success.
Strong understanding of software development best practices, including testing, git, code reviews, and model lifecycle management.
Working with Docker containers to support reproducible and scalable environments.
Experience with real time systems and stream processing is desirable.
Basic understanding of machine learning is required.
Familiarity with Control Theory concepts (feedback loops, PID, or MPC) to manage dynamic supply/demand signals is beneficial.
Experience in the logistics domain is also beneficial.
What will you bring to the table?
Systems Thinking: You intuitively understand feedback loops and second-order effects in complex networks.
Leadership and mentorship skills, with the ability to guide and develop junior data scientists and foster team collaboration.
A holistic project approach, from generating business cases to managing the full lifecycle of models.
Ability to generate innovative ideas, test hypotheses rigorously, and pitch business cases to stakeholders.
Critical analysis of approaches, assumptions, and business impact, with the ability to challenge and refine strategies for optimal results.
Preference for simple, scalable, and effective solutions, particularly in complex projects.
Expertise in agile environments with strong collaborative skills, particularly in cross-functional teams.
Excellent communication skills, including the ability to present complex data insights and OR concepts to a wide range of stakeholders, both technical and non-technical.
hackajob is partnering with Just Eat to fill this position. Create a profile to be automatically considered for this role—and others that match your experience.