Overview
Data Science Lead Jobs in Egypt at دويليو | Dwelleo
Title: Data Science Lead
Company: دويليو | Dwelleo
Location: Egypt
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.