Advanced degree (Ph.D. preferred) in engineering, science, mathematics or related subjects
Expert knowledge of statistical programming languages such as R or Python, and SQL.
Readiness to work with engineering teams to develop prototypes of software products leveraging exploratory data analytics.
Expert knowledge of data visualization, using tools such as Tableau or PowerBI.
Expert knowledge of Experimental Design and Statistical Decision Theory.
Solid knowledge of distributed data storage and computing, including Hadoop or Cassandra.
Practical knowledge of cloud computing, including AWS (preferred) or Azure and highly scalable databases, such as Dynamo DB.
Knowledge of NoSQL databases, such as MongoDB.
Great communication skills in English.
5+ years working and communicating with business stakeholders as a trusted adviser in data science.
5+ years translating business requirements into data science problem statements and execution tasks.
In-depth understanding of the machine learning lifecycle.
Practical skills with agile software development methods such as Scrum and Kanban

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