Associate Data Scientist
Aera Technology
Full Time1+ yearsPosted 17 days ago
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Overview
Position Type
Full Time
Experience
1+ years
Job Description
Responsibilities
- 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).