I need clear, data-driven answers on how Netflix viewers engage with individual movies and series. The dataset is ready to share and covers title-level watch events (start time, stop time, device, account ID, etc.). My goal is to identify which titles truly hold attention, where audiences drop off, and what patterns separate high-engagement content from the rest. Scope of work • Clean and prepare the raw viewing logs so episode, season and movie records line up neatly. • Calculate engagement-centric metrics for every title—think average minutes watched per play, partial vs. full completions, repeat sessions, and binge streaks. • Visualise the results with clear charts that spotlight standout performers and weak links. A Tableau or Power BI dashboard that lets me slice by date range, genre tag and device would be ideal, but well-structured Python notebooks with Matplotlib / Seaborn visuals are fine too. • Summarise key insights in a short, plain-English report that I can present to non-technical stakeholders. Acceptance criteria – Reproducible code (Python, R or SQL) delivered with comments so I can rerun it on fresh data. – Cleaned dataset and calculated fields supplied in CSV or Parquet. – At least five meaningful visualisations highlighting user engagement per content title. – Executive summary (PDF or slide deck) capturing the main takeaways and recommended next steps. If you have proven experience dissecting streaming-platform logs or large-scale behavioural data, I’m ready to get started right away.