York Towers is the development arm of the York Holding Group. Through continuous research and the ability to predict emerging trends, the company keeps an edge over the market. Playing a leading role in driving the successful development and diversification of one of the most vital economic sectors, York Towers is committed to creating residential products across the country that provide residents with distinctive, universal, multicultural, and enriching lifestyles. York Towers is the exclusive developer of luxury real estate worldwide. The company aims to become a leading real estate player through an efficient business model and advanced technologies used for designing and construction. Since its establishment in 2016, York Towers has delivered 20 real estate properties and runs six dynamic projects. York Towers operates eight offices in five countries across three continents.
We're looking for an experienced Data & Market Intelligence Lead to drive the strategy, architecture, and delivery of our data intelligence capabilities. This is a hands-on leadership role for someone who combines deep machine learning expertise with strong execution, taking ownership of production ML systems, market data strategy, and the growth of the Data & Market Intelligence function.
You'll play a critical role in designing scalable machine learning infrastructure, transforming data into actionable intelligence, and ensuring our models are robust, explainable, and production-ready from day one.
Responsibilities:
- Define the modelling roadmap and make build-vs-buy calls across model types (the platform leans AWS — SageMaker, Personalize where it fits).
- Solve the cold-start problem: design models that perform with sparse first-party data at launch, and lead the strategy for acquiring, scraping, and licensing external market data (REGA, public records, macroeconomic indicators, third-party listing data).
- Own the full MLOps lifecycle: data and feature pipelines, model registry and versioning, automated training/retraining, CI/CD for models, model serving, and live monitoring for drift, data quality, and performance — with reproducibility and rollback built in, not bolted on later.
- Architect every AI service as a highly scalable, low-latency API built to serve the platform at production scale (the roadmap targets 100k users and millions of inference requests a month), with horizontal scaling, caching, batching, and inference-cost control designed in from day one.
- Establish ground truth and evaluation — accuracy targets, drift monitoring, and how each score is validated and explained to users.
- Ensure PDPL compliance and anonymisation for any insights derived from user data; partner with the platform team on data governance.
- Expose models as clean APIs the Laravel/TypeScript platform team can consume without touching Python.
- Recruit, lead, and hold accountable the Data & Market Intelligence chapter as the function scales.
What You Bring
Technical Depth:
- 7+ years in ML/data science with real production model ownership, and prior team leadership.
- Strong applied background in regression, time-series forecasting, and scoring/ranking — ideally pricing, valuation, demand, or risk models.
- Hands-on Python ML stack (pandas, scikit-learn, plus deep-learning frameworks).
- Strong, hands-on MLOps — has stood up production ML infrastructure end to end: experiment tracking, model registry/versioning, automated retraining and evaluation, containerised serving, monitoring/alerting (drift, latency, accuracy), and infrastructure-as-code. On AWS this means comfort with SageMaker (pipelines, model registry, endpoints) or an equivalent self-managed stack.
- Proven experience designing high-throughput, low-latency ML serving at scale — load-aware architecture, autoscaling, caching/feature reuse, and keeping inference cost and latency under control as volume grows.
- Cloud ML at production scale (AWS strongly preferred).
- Comfort operating in a data-scarce, build-from-zero environment — pragmatic about heuristics/algorithmic baselines before full models.
- Preferred: real estate / proptech, fintech, or marketplace pricing experience; geospatial modelling and external data licensing; familiarity with Saudi/GCC market and data sources (REGA, Suhail); Arabic language; KSA data residency and regulatory awareness.
Leadership & Execution:
- A strict, execution-driven manager — sets clear standards, owns deadlines, and holds the team accountable to them.
- Decisive and hands-on; leads by delivering, not delegating-and-hoping.
- Comfortable enforcing quality bars on code, models, and process.
- Pragmatic prioritiser who can ship a working baseline under data and time constraints rather than chasing perfection.
- Clear communicator who can explain model behaviour and trade-offs to non-ML stakeholders (product, platform, executives).
If you're ready to shape and scale data intelligence capabilities in a high-growth environment, we'd love to hear from you.
