Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity, and computer architecture

Use exceptional mathematical skills, in order to perform computations and work with the algorithms involved in this type of programming

Produce project outcomes and isolate the issues that need to be resolved, in order to make programs more effective

Collaborate with data engineers to build data and model pipelines

Manage the infrastructure and data pipelines needed to bring code to production

Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created

Build algorithms based on statistical modeling procedures and build and maintain scalable machine learning solutions in the production

Use data modeling and evaluation strategy to find patterns and predict unseen instances

Apply machine learning algorithms and libraries

Communicate and explain complex processes to people who are not programming experts

Liaise with stakeholders to analyze business problems, clarify requirements and define the scope of the resolution needed

Analyse large, complex datasets to extract insights and decide on the appropriate technique

Research and implement best practices to improve the existing machine learning infrastructure

Provide support to engineers and product managers in implementing machine learning in the product.