Explore datasets to identify trends, patterns, and anomalies across the customer lifecycle.
Analyse data to answer more complex product, growth, and business questions.
Present findings clearly, focusing on the story behind the data and what it means for decision-making.
Partner with product managers, engineers, and other teams to refine questions and iterate on insights.
Build dashboards and reports that surface trusted metrics and enable product, finance, and growth teams to explore data with confidence.
Build reusable analytical models that support consistent reporting and repeatable analysis.
Work closely with data engineers to understand data models, definitions, and data quality constraints.
Document data definitions, table structures, and common analysis patterns.

Requirements

Experience working with SQL to query and analyse real-world datasets.
Working knowledge of Python (Pandas or similar), for analysis and modelling.
Experience building or contributing to dashboards and visualisations.
A clear, practical understanding of basic data modelling concepts, such as fact tables, dimension tables, and star schemas.
Demonstrated ability to communicate analytical findings clearly to both technical and non-technical audiences.
Motivation to help others succeed with data, not just complete tickets or deliver reports.
Confidence working independently on well-scoped analysis, with good judgement about when to ask for help.
Curiosity, a learning mindset, and an interest in how data informs product and business decisions.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonPandasdata modellingdashboardsvisualisationsanalytical modelsdata analysisdata qualityreporting

Soft Skills

communicationcollaborationindependencecuriositylearning mindsetproblem-solvingmotivationjudgementanalytical thinkingstorytelling