Contract / secondment role. Initial term 6–12 months, with scope to extend.
A leading Hong Kong real estate group is bringing in an experienced Data Scientist on a contract basis to strengthen its Data Analytics function. This is a hands-on delivery seat: you'll own models end to end, from framing the problem with the business through to running them in production.
What you'll be doing
You'll build and refine machine learning models that feed real commercial decisions, and you'll be judged on whether those models actually hold up in production, not just in a notebook. Day to day that means:
- Improving existing models through disciplined performance testing and honest impact measurement
- Working alongside the IT function to get models deployed, then keeping them healthy with repeatable evaluation and monitoring pipelines
- Choosing the right algorithm for the problem and defending that choice with sound mathematics, adapting where the data, tooling or platform demands it
- Writing production-grade, maintainable code with sensible repo structure, tests, documentation and peer review
- Sitting with business stakeholders to turn loose, ambiguous questions into something technically answerable, then explaining what the results mean in plain language
What we're looking for
- Degree in Computer Science, Statistics, Mathematics, Econometrics, Operations Research or a comparable quantitative field
- At least 4 years hands-on in data science, including models you have genuinely shipped and then maintained in production
- Strong Python and PySpark, plus solid SQL
- Practical MLOps exposure: versioning, experiment tracking, CI/CD, monitoring and drift detection
- Comfortable across mainstream algorithms (XGBoost, neural networks, KNN and similar) and able to justify why one fits over another
- Familiar with proper engineering practice, including code reviews and pull requests
- Testing frameworks such as pytest
- Azure and Azure Databricks experience is a strong advantage
- Agile ways of working and tools like Jira are a plus
- Clear communicator who can pitch the same idea to an engineer and to a non-technical director without losing either of them
Why consider it
You'll join a mature analytics team where data science is treated as a delivery discipline rather than a side experiment, with visible business problems and stakeholders who want the answers.