Job Description

We think of AI in the broadest sense and have data scientists that are specialized in time series, machine learning and/or operations research. Data scientists who are happy and thrive in our team, all have these elements in common: 

• they are motivated to have a broad impact and work on real world problems
• they are excited to translate academic knowledge into pragmatic solutions
• they love to learn while working: through the variety of scientific and business challenges they face, through their contact with peers and weekly touchpoints with our world renowned scientific advisors
• they like being exposed to all sorts of different business problems and various aspects of a project: business problem understanding, data gathering, cleaning and analysis, model development, paper reading, presentation of results, documentation, productionisation, etc.
• they like thinking about the best way to communicate proposed approaches,  results and finding
• they continuously seek ways of improving the way we work and to make everyone around them achieve their full potential.

Of course, none of this is done by a data scientist alone, and as a data scientist, you will be part of a wider and  agile cross-functional team (consultant, developers, data scientists and scientific advisors) formed to deliver our bespoke client’s solutions.

Required Skills and Competencies 

• Capacity to work in a team
• Openness to be exposed to new tools, business domains and scientific fields.
• Capacity to learn and seek the required tools and support to do so.
• Expertise in one or more of the AI and/or data science applied areas, e.g., operations research, optimization, time series analysis, classic machine learning, natural language processing, computer vision, etc.
• Expertise in one or more of the prominent AI/data science techniques, e.g., linear/dynamic programming, neural networks/deep learning, reinforcement learning, advanced statistics, probability, information theory, optimization, complex systems, Markov chains, game theory, Monte-Carlo methods, etc.
• Well versed in the AI/data science landscape of technology tools, platforms and related service provider ecosystem.
• For machine learning focused data scientists
  • Experience in data wrangling using one or more of the modern programming languages/frameworks (e.g., Python, Pandas, Numpy, SQL, NoSQL)
  • Experience implementing AI/data science algorithms using one or more of the modern ML frameworks (e.g., Scikit-learn, Tensorflow, Keras, PyTorch, LightGBM, XGBoost, CatBoost, Caffe, MxNet,  Statsmodels, etc.).
  • Experience implementing AI/data science algorithms using one or more of the modern ML frameworks (e.g., Scikit-learn, Tensorflow, PyTorch, LightGBM, XGBoost,  Prophet, PyMC3, Statsmodels.).
• For operations research focused data scientists
  • Experience implementing optimization algorithms using mathematical programming solvers (cplex, gurobi, xpress, cbc, ipopt) or constraint programming solvers (CP Optimizer,  CP-SAT) via application programming interfaces (concert, c callable library, pyomo, etc.)  
• Drives adherence to quality standards of work

Nice to have Skills and Competencies 

• Experience working on Supply Chain Management, Logistics or Transportation related software applications
• Experience working in an Agile development environment 
• Experience working with one or more of the cloud computing platforms: GCP, Azure, AWS
• Experience working with one for more of the software version control systems/tools: Git, SVN, etc.
• Experience or exposure to both operations research and machine learning
• Experience developing optimization solutions in C/C++