I’m looking for an experienced Data Analyst / Data Scientist with AdTech or performance analytics background to support a short-term data analysis task. The project involves analysing a provided impression-level dataset (CSV) containing user, device, and contextual information over a one-month period. The goal is to extract insights, assess monetisation performance, and define features for a conversion prediction use case. This is a one-off analytical task, expected to take 3–4 hours for someone experienced. Scope of Work The work includes: SQL-based analysis Calculate IPM (Installs per Mille) per country using SQL only. Identify top-performing segments. Performance & risk analysis Assess risks of scaling budget on top-performing demand apps. Highlight biases, stability concerns, and data limitations. Feature definition for conversion prediction Propose: 3 contextual features 3 behavioural features Explain why they are useful. Feature engineering Write Python code to calculate the features. Explain risks such as leakage, bias, or instability. Visualization Create one presentation-ready chart showing how a contextual and behavioural feature relate to conversion rate. Audience: Head of Product / non-technical stakeholders. Delivery Jupyter Notebook or ZIP containing: Code Clear written explanations Final visual No raw dataset should be included in the final delivery.