Associate Data Scientist - Optimization & Operations Research
Aera Technology
Aera Technology is the Decision Intelligence company. We deliver innovation and services that enable enterprises to operate sustainably, intelligently, and efficiently. Our platform, Aera Decision Cloud™, integrates with your existing systems to digitize, augment, and automate decisions in real time. Aera helps enterprises around the world transform decision making – delivering millions of recommendations that have resulted in significant revenue gains and cost savings for some of the world’s best-known brands.
We are looking for an Associate Data Scientist with exceptional strength and deep interest in Operations Research and mathematical optimization. In this role, you will turn complex planning, pricing, and supply chain problems into well-structured optimization models and help design algorithms that run at scale in real customer environments.
Responsibility
Work with real-world business data to formulate optimization problems in areas such as supply chain, inventory, production planning, and pricing.
Design, implement, test, and refine linear, integer, and mixed-integer programming models, along with heuristic or meta-heuristic approaches where needed.
Prototype and compare alternative formulations and solution strategies, balancing optimality, robustness, and runtime performance.
Use commercial and open-source solvers (e.g., Gurobi, CPLEX, COIN-OR) effectively, including model diagnostics, tuning, and performance analysis.
Collaborate with solution delivery and data engineering teams to integrate optimization models into end‑to‑end decision workflows.
Engage with customers and internal stakeholders to understand requirements, explain model behavior and trade-offs, and iterate on designs.
About You
Bachelor’s or Master’s degree in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or a related quantitative field.
1-3 of experience in optimization / OR, including internships, academic projects, or industry experience; outstanding fresh graduates are encouraged to apply.
Strong foundations in linear algebra, probability, optimization theory, and algorithms, with clear intuition for LP/MIP modeling.
Hands-on experience formulating and solving optimization models using at least one solver (Gurobi, CPLEX, COIN-OR, etc.) and one programming language (preferably Python).
Demonstrated passion for OR: coursework, theses, competitions, or open-source contributions.
Ability to reason from first principles, question assumptions, and propose alternative formulations when the first approach does not work.
Comfortable working in a fast-paced environment, taking ownership, and learning new problem domains quickly.
Nice to Have
Exposure to supply chain, logistics, or pricing optimization problems.
Experience with large-scale data handling (SQL, Spark, or similar) to prepare input data for optimization runs.
Familiarity with building small services or scripts to operationalize optimization runs (e.g., scheduling, APIs, or batch jobs).