Bachelors, Masters or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
8+ years of deep technical experience in distributed computing, machine learning and statistics related work
Programming experience in languages such as Python, R, Scala, SQL
Knowledge of distributed computing or NoSQL technologies is a plus
Proven application of advanced analytical, data science and statistical methods in the commercial world
Client-facing skills (e.g. working in close-knit teams on topics such as data warehousing, machine learning)
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.
Thought leadership or people leadership experience (e.g. managed project teams or direct reports)
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.
Willingness to travel
Good presentation and communication skills with a knack for explaining complex analytical concepts to people from other fields
Strong communication skills, both verbal and written, in English and Portuguese, with the ability to adjust your style to suit different perspectives and seniority levels
