Senior Data Scientist Needed

I’m gearing up for a data-driven initiative that spans the full spectrum—from raw ingestion through insight delivery—and I want a senior-level data scientist to steer the technical work. The scope is intentionally broad right now because I’m still gathering business requirements, but the essentials are clear:

• You’ll clean, explore, and engineer features from whatever data sources we finalise (they may include structured tables, free-text logs, images, or time-series feeds).
• When the data story warrants it, you’ll build and validate predictive or prescriptive models in Python or R, leveraging libraries such as pandas, scikit-learn, TensorFlow, Prophet, or similar.
• Clear, decision-ready output matters, so expect to create concise visualisations or dashboards—Tableau, Power BI, or matplotlib/Plotly—alongside well-annotated notebooks and a short slide deck summarising key findings.
• Every step should be reproducible. Please version your code in Git and containerise any complex environments with Docker so I can run everything on my end without guesswork.

Deliverables I’ll review for acceptance
1. A Git repository containing notebooks/scripts, modular functions, and a README that explains setup and usage.
2. A standalone model artefact (if modelling is required) with instructions for retraining and inference.
3. A share-link or packaged dashboard plus a brief report (5–10 slides) highlighting insights, limitations, and next steps.

I’m happy to iterate on requirements as we refine the problem statement together, but I need someone who is comfortable making the first technical moves with limited upfront direction and who communicates clearly about assumptions, risks, and trade-offs. If that sounds like you, let’s get started.