Description

Develop prescriptive analytics models and proof-of-concepts to solve complex business problems.

Responsibilities

• Define data science use cases, propose modeling approaches, and estimate data requirements and project effort.
• Build proof-of-concept models by acquiring, cleansing, and harmonizing data to identify appropriate optimization algorithms.
• Develop interpretable, explainable, and scalable models that meet specific business needs.
• Communicate findings and actionable insights to stakeholders and senior leadership through visualizations and interactive dashboards.
• Collaborate with Enterprise AI/ML and DTS Delivery teams to scale high-value models into production.

Required Skills

• 3+ years of hands-on experience in data science projects.
• Proficiency in SQL and at least one programming language such as Python, R, C++, MiniTab, SAS, Matlab, or VBA.
• Experience with machine learning methods including multivariate regression, feature engineering, random forests, XGBoost, elastic nets, hierarchical Bayesian regression, or unsupervised learning/clustering.
• Practical or theoretical experience in mathematical optimization techniques like linear/non-linear optimization, mixed integer programming, or constraint programming.
• Proficiency in data visualization tools such as Power BI, Tableau, Qlik, D3, or Shiny.
• Bachelor’s degree in a quantitative field such as Engineering, Computer Science, Statistics, Economics, or Mathematics.
• Ability to make reasonable assumptions to progress projects when working with incomplete data.

Preferred Skills

• Advanced degree in a quantitative field.
• Experience in CPG, Retail, Digital Marketing, E-commerce, or Revenue Management.
• Knowledge of optimization engines such as CPLEX or Gurobi.

Key Skills

Education

Not specified