Required:

* 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:

* 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.