Choose candidate features for a churn model and check each for leakage.
Data and Analytics
Skills for exploring, querying, profiling and explaining data.
Clean a messy spreadsheet by standardising values, removing blanks and splitting combined fields.
Reconcile two sources of the same figure and explain any remaining difference.
Define freshness checks that alert when a dataset is older than expected.
Summarise an analysis for executives: the answer, the confidence and the recommended action.
Clarify and prioritise a data request by the decision it supports and the effort it needs.
Generate realistic sample data for testing that contains no real personal information.
Find columns that probably hold personal data based on their names and sample values.
Write a data contract for a dataset covering schema, freshness, quality and ownership.
Review a metric definition for ambiguity, double counting and mismatched time windows.
Write a tracking specification that engineers can implement without guessing.
Plan product analytics events with names, properties, triggers and owners.