Operations Research Scientist
1 month ago
Job Description:
As an Operations Research Scientist at Tredence, you will:
1. Perform Data Analysis and Interpretation:
o Analyze large datasets to extract meaningful insights and support decision-making processes. Use Python to process, visualize, and interpret data in a clear and actionable manner.
2. Develop and Implement Models:
o Create mathematical models to address complex business problems and improve operational efficiency. Ability to use solvers like CPLEX, Gurobi, FICCO Xpress. Free solvers like Pulp, Pyomo etc.
o Apply optimization techniques and heuristic methods to devise effective solutions.
o Design and implement algorithms to solve optimization problems and enhance existing systems with advanced techniques like column generation, decomposition techniques
o Test and validate algorithms to ensure accuracy and efficiency.
3. Collaboration and Communication:
o Work closely with cross-functional teams including data scientists, engineers, and business stakeholders to understand requirements and deliver solutions.
o Present findings and recommendations to both technical and non-technical audiences.
Qualifications:
· Education: Bachelor’s or master’s degree in operations research, Applied Mathematics, Computer Science, Engineering, or a related field.
· Experience: 1-2 years of professional experience in operations research, data science, or a related field.
· Technical Skills:
o Proficiency in Python, including libraries such as NumPy, pandas, SciPy, and scikit-learn, Pulp, Pyspark
o Strong background in mathematical modeling and optimization techniques.
o Experience with heuristic methods and algorithm development.
· Analytical Skills:
o Ability to analyze complex datasets and derive actionable insights.
o Strong problem-solving skills with a detail-oriented approach.
· Soft Skills:
o Excellent communication skills, both written and verbal.
o Strong team player with the ability to work independently and manage multiple tasks.
Preferred Qualifications:
· Experience with additional programming languages or tools (AMPL, LINGO, AIMMS).
· Familiarity with machine learning techniques and their applications in operations research.
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