Key Skills:Statistical Modelling, Data Science, Linear Regression, Gurobi, CPLEX-IBM, Core Python Programming, SQL
Roles and Responsibilities:
- Identify operational problems and improvement opportunities using quantitative methods and business analysis.
- Gather, clean, and analyze structured and unstructured data from multiple sources.
- Develop mathematical, statistical, and machine learning models to support decision-making.
- Create and validate decision support tools and automated analytics solutions.
- Collaborate with cross-functional teams to define requirements and implement data-driven recommendations.
- Prepare visualizations, reports, and presentations to clearly communicate insights to stakeholders.
- Monitor implemented solutions and continuously refine models based on real-world performance.
Skills Required:
- Strong proficiency in statistical modeling and quantitative analysis
- Expertise in linear regression, predictive modeling, and data science methodologies
- Hands-on experience with Core Python programming for data analysis and model development
- Proficiency in SQL for querying and managing structured data
- Knowledge of optimization solvers such as Gurobi and CPLEX-IBM for mathematical modeling
- Experience with data preprocessing, cleaning, and validation
- Familiarity with machine learning algorithms and frameworks
- Ability to translate business problems into analytical models and actionable insights
- Strong experience in decision support tools, dashboards, and data visualizations
- Excellent problem-solving, communication, and stakeholder management skills
- Experience working in cross-functional teams and delivering end-to-end data science solutions
- Knowledge of statistical testing, hypothesis testing, and operational research methods
Education:Bachelor's Degree in Operations Research, Industrial Engineering, Applied Mathematics, Data Science, Statistics, or a related field
