Identify problems, deconstruct them into manageable modules/steps, frame relevant questions, assess informational needs in service to answering these questions, and contextualize approaches to a data science task.

Understand the role of the data scientist as a data steward and be able to effectively acquire and transform large data sets for use with various data mining and machine learning and inferential reasoning techniques. Present/visualize the outputs of such algorithms appropriately.

Use statistical modeling techniques and construct/evaluate machine learning algorithms. Evaluate and interpret models, and understand their qualitative and quantitative advantages and limitations.

Effectively communicate data science-related information analyses to both technical and non-technical audiences.

Understand the value and necessity of safeguarding data, privacy, and the ethical use of data.

Undertake situational analysis and needs assessments to identify and employ the most appropriate analytical or applied research strategies for pursuing a question or set of questions relevant to an organization.