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Build the brain that powers Archer’s on-demand Urban Air Mobility (UAM) service. Shape the intelligence layer of a revolutionary transportation network.
Job Responsibility:
Design and implement decision-making engines that optimize aircraft routing, fleet allocation, and network responsiveness under dynamic demand and operational constraints
Develop and deploy production-level optimization and machine learning models that operate in near real-time, directly impacting network efficiency and customer experience
Partner closely with Product, Engineering, and Operations teams to translate complex business requirements into scalable, robust data science solutions
Develop sophisticated simulation environments to test and validate algorithmic strategies, ensuring system reliability before real-world deployment
Conduct deep-dive analyses to uncover strategic insights that will inform the product roadmap and long-term business strategy, presenting your findings to leadership
Champion data science best practices and mentor other team members, helping to define the technical culture and standards for the group
Requirements:
MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field
Strong data engineering principles familiar with technologies to store, query, process, and analyze data
5+ years experience implementing optimization, ML, or AI models
Strong programming skills in languages like Python, C/C++, Java, or Go
Experience driving novel insight through custom data analytics and machine learning
Creative mind who can identify new and creative problems in addition to executing against known ones
A passion for urban mobility, sustainable transportation, and the future of cities
Nice to have:
5+ years of software engineering experience
Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications
Prior experience with transportation systems, especially within aviation
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