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Job title:
Data Scientist - Optimization Expertise
Job Purpose:
Conduct research and development on mathematical algorithmic estimation tools for causal inference models. Using the results from predictive causal inference models, develop accurate simulation models and optimization algorithms that broadly and deeply inform clients the future budgeting outlays and planning decisions.
Key Responsibilities
- Develop, implement, and test mathematical modeling and optimization algorithms to answer complex business questions.
- Create various prototypes for research and development purposes.
- Design, write and test modules for Nielsen analytics platforms using Python, R, SQL, Spark, C# and AWS products.
- Utilize advanced computational/statistics libraries including Spark MLlib, Scikit-learn, SciPy, StatsModels, SAS and R.
- Utilize optimization solver including Gurobi and NAG.
- Partner with the Nielsen Technology department to build best-of-class cloud-based analytical solutions.
- Document methodology.
Key Skills
- PhD level mathematical optimization coursework, knowledge of optimization theory. Ability to interpret academic research papers and apply methodologies.
- Expertise in Python.Expertise in using CVXOPT, Gurobi and Numerical Algorithm Groups solvers.
- Experience writing production grade code using open-source scientific computing packages (e.g., R, Apache Spark Machine Learning Library MLlib, NumPy, Scipy Sklearn)
- Well-organized and capable of handling multiple mission-critical projects simultaneously while meeting deadlines.
- Exceptional problem-solving skills.
- Excellent oral and written communication skills.
Requirements
- Graduate degree in Operations Research, Industrial Engineering, Applied Mathematics, or other Quantitative Field of Study.
- 2+ years’ experience in delivering optimization solutions.
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