Operations Research Engineer- Marketplace
Swvl is a revolutionary idea that was born from passion, loyalty, and persistence to face all challenges that come our way. It started with an observation turning into a realization; too many cars on the streets, wasting our limited resources: time, space, and money.
In 4 years Swvl became the first 1.5 billion unicorn in the Middle East to list on NASDAQ and currently the 2nd best-funded startup in the MENA region. With a presence and operations in up to 10 countries worldwide and a vision to be active on 6 continents.
Our main goal is not just to facilitate commuting, but a hunger to strive for solutions, encourage the contribution of youth in innovation, and inspire change.
We are looking for an enthusiastic Engineer to join our team.
About Marketplace Tribe:
Marketplace is the platform that connects customers and captains. Our goal is to be reliable, profitable, and scalable. We do this by focusing on ETAs (Estimated Time of Arrivals), pricing, dispatching, supporting multiple choices of rides, and the network’s efficient coverage growth.
Responsibilities and Duties:
- Apply academic research to Swvl’s different problems.
- Design and implement creative proofs of concepts (PoCs).
- Work with complex mathematical models and use graph, search, computational geometry or other related algorithms.
- Solve optimization problems using techniques like metaheuristics, linear programming, constraint programming, etc.
- Analyze data, extract meaningful insights and draw conclusions.
- Conduct experimentation and evaluation of research outcomes and proposed solutions.
- Formulate and contribute to identifying Swvl’s short-term and long-term problems.
- Contribute directly to Swvl’s products from the business needs to the final delivery.
- BSc. in Computer Science, Engineering, or a relevant field.
- 0-3 years of industry experience
- Strong problem-solving and analytical skills.
- Very good research skills.
- Knowledge of advanced algorithms and optimization theory is a huge plus.
- Background in data science: data analysis, machine-learning methods, statistical modelling is a plus.
- Sufficient coding and design concepts.
- Functional Skills.
- Excellent communication skills.
- Ability to apply knowledge in real-life problems.
- Very good reasoning and logical thinking.
- Creative and outside-the-box thinking.
- Business acumen is a plus.
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