Bachelors, Masters or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
Professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
Programming experience (focus on machine learning): R and/or Python (must), SPSS, SAS, Ruby, Hadoop (valued)
Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
Ability to independently own and drive model development, balancing demands and deadlines
Demonstrated aptitude for analytics
While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
Willingness to travel
Good presentation and communication skills, with the ability to explain complex analytical concepts to people from other fields
Strong communication skills, both verbal and written, in English, with the ability to adjust your style to suit different perspectives and seniority levels. Knowledge of French or Dutch is valued
