Operation Research Analyst

Overview

On Site

$40,000 - $60,000

Full Time

Skills

Advanced Analytics

Applied Mathematics

Analytical Skill

Business Intelligence

Critical Thinking

Decision Support

Forecasting

Data Analysis

Data Science

Google Cloud Platform

Collaboration

Cloud Computing

Good Clinical Practice

Machine Learning (ML)

Operations Research

Programming Languages

Optimization

Microsoft Power BI

Job Details

Key Responsibilities

1. Data & Problem Analysis

Identify business challenges and opportunities that can be addressed through operations research and quantitative analysis.
Collect, clean, and prepare datasets from multiple internal and external sources.
Analyze processes, workflows, and performance metrics to determine operational bottlenecks and improvement areas.

2. Modeling & Optimization

Develop optimization models, simulation models, forecasting models, and statistical analyses.
Apply linear programming, integer programming, stochastic models, queuing theory, and other OR techniques.
Run scenario analyses, sensitivity tests, and what-if modeling for strategic planning.

3. Decision Support

Create dashboards, reports, and visualizations to translate analytical findings into actionable insights.
Present results, recommendations, and decision-support tools to business leaders.
Collaborate with operations, finance, supply chain, and technology teams to implement solutions.

4. Tool & Technology Use

Utilize advanced analytics tools such as Python, R, MATLAB, SAS, or Julia.
Work with optimization solvers (Gurobi, CPLEX, OR-Tools, etc.).
Use BI tools like Tableau, Power BI, or Qlik for reporting and visualization.

5. Continuous Improvement

Identify new opportunities to apply OR techniques across the organization.
Monitor model performance and refine models based on changing requirements.
Stay updated with emerging OR methodologies, algorithms, and industry best practices.

Required Qualifications

Bachelor s or Master s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Data Science, Economics, or related field.
Strong understanding of optimization, simulation, probability, and statistical methods.
Experience with data analytics and mathematical modeling.
Proficiency in programming languages (Python, R, or similar).
Familiarity with optimization solvers and analytical tools.
Strong problem-solving and critical-thinking skills.
Ability to communicate complex concepts to non-technical stakeholders.

Preferred Qualifications

Experience in supply chain, logistics, manufacturing, finance, or relevant industry.
Knowledge of machine learning techniques.
Experience working with large-scale datasets and database querying (SQL).
Exposure to cloud platforms (AWS, Azure, Google Cloud Platform) is a plus.

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