Required Qualifications: 

M.Sc. in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations Research or similar applied quantitative field                       

• 4-8 years of industry experience in developing production-grade statistical and machine learning code in a collaborative team environment.

• Prior experience in machine learning using R or Python (scikit / numpy / pandas / statsmodel).

• Prior experience in time series forecasting.

• Prior experience with typical data management systems and tools such as SQL.

• Knowledge and ability to work within a large-scale computing or big data context, and hands-on experience with Hadoop, Spark, DataBricks or similar.

• Excellent analytical skills; ability to understand business needs and translate them into technical solutions, including analysis specifications and models.

• Creative thinking skills with emphasis on developing innovative methods to solve hard problems under ambiguity and no obvious solutions.

• Good interpersonal and communication (verbal and written) skills, including the ability to write concise and accurate technical documentation and communicate technical ideas to non-technical audiences. 

Preferred Qualifications: 

•PhD in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations Research or similar applied quantitative field.

• Experience in machine learning using R or Python (scikit / numpy / pandas / statsmodel) with skill level at or near fluency.

• Experience with deep learning models (e.g., tensorflow, PyTorch, CNTK) and solid knowledge of theory and practice.

• Practical and professional experience contributing to and maintaining a large code base with code versioning systems such as Git.

• Knowledge of supply chain models, operations research techniques, optimization modelling and solvers.