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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent, full-time |
Responsibilities include: • Identification and prioritisation for projects in a dynamic environment, with a keen eye for where maximum value can be delivered. • Applying machine learning models / optimization in creative ways to heterogeneous data sets. • Taking concepts from POC into production • Always seeking new ways, us utilising data and modelling into the day-to-day inner workings of the commodities industry. Qualifications: Essential: • MSc or PhD level Computer Science, Machine Learning, Applied Statistics, Mathematics. • 3-5 years of hands-on experience in applying data science methods to real-world business problems. • Experience of getting the best results from messy data sets • Python (3), high level of capability in writing understandable / extensible /well-documented code. • Experience of data storage platforms (SQL, NoSQL, Map-Reduce frameworks, etc.) • Attention to detail / thirst for real answers from data (how, why, what, when) • Experience presenting data visually (Plotly, D3, Tableau). Preferred: • Time series modelling (ML / econometrics) • Enterprise software development (code design, review, gitflow, etc.) • Cloud-based data science workflows (on AWS in particular) • Deep Learning (able to translate deep learning models). People Skills: • Self-Motivation / discipline • People first / natural collaboration skills • Methodical / rigorous / daring • Able to work independently and in teams and with all levels of an organisation • Team player / unpolitical working style • The desire to be a thought-leader / partner and make a serious impact on the bottom line of the company (energy flows)