Key Responsibilities:
- Lead and execute data science projects focused on operational optimization from concept to deployment
- Design and implement mathematical models to improve process performance, decision-making, and resource utilization
- Apply linear programming, mixed-integer programming, and heuristic/metaheuristic techniques to real-world problems
- Collaborate with cross-functional stakeholders to define project objectives and translate them into data-driven solutions
- Develop data pipelines and apply statistical and machine learning methods to derive insights
- Clearly communicate technical solutions and findings to both technical and business audiences
- Mentor junior team members and contribute to the growth of internal best practices and knowledge sharing
Required Skills and Qualifications:
- Master's or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related field
- Minimum 8 years of hands-on experience in data science with a strong focus on optimization
- Proficient in Python (NumPy, Pandas, SciPy, Scikit-learn) and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX
- Strong SQL skills and experience building and working with robust data pipelines
- Proven experience delivering end-to-end internal optimization solutions
- Excellent problem-solving and analytical skills
- Strong communication and stakeholder engagement skills
Preferred Qualifications:
- Experience with internal optimization projects in logistics, cost reduction, workforce/resource planning
- Familiarity with Databricks, Azure ML, or AWS SageMaker
- Working knowledge of dashboarding tools such as Power BI or Tableau
- Prior experience in consulting environments or internal Centers of Excellence (CoEs)
