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Specialist (Data Science)

Raya Holding • Wholesale • Systems Integrators • Bachelor's Degree • Python • SQL • 2 months ago
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Salary
≈ $63k – $172k per year (Estimated)
Location
In office (Egypt)
Seniority
Middle · 3+ years exp

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Aug 16, 2026.

Overview
Company
Impact
Profile match

Raya Holding

Raya Holding is an Egyptian group founded in 1999 and headquartered in Cairo. Its subsidiaries cover information technology, contact centres, distribution and logistics. The company is listed on the Egyptian Exchange.
rayacorp.com • HQ: Cairo, Giza, Egypt • Wholesale • Call Center Services • Systems Integrators • 501-1000 employees • Est. 1999
Tech stack of Raya Holding
  • End-to-end ownership of models - from framing new projects and data work through deployment, monitoring, and retraining, as well as owning models already in production.
  • Scoping and kicking off new projects - problem framing, data exploration, and initial modeling - not just maintaining what's already shipped.
  • Code review for the Data Science team: setting and enforcing standards for readability, testing, and maintainability across everyone's PRs, not just your own.
  • CI/CD for model and pipeline code - build, test, and deployment pipelines that let the team ship changes safely and often.
  • Production reliability - monitoring, alerting, and incident response for models you and your squad own once they're live.
  • Mentoring less senior team members on both modeling judgment and software engineering practice.
  • Strong computer science fundamentals: clean, well-tested, version-controlled code - not notebook-only work.
  • Hands-on CI/CD experience: building and maintaining pipelines (e.g. GitHub Actions, GitLab CI, Jenkins, or similar).
  • Real MLOps experience: model packaging, deployment, monitoring, and retraining in production - not just training a model and handing it off.
  • A versatile, generalist data science background: comfortable moving across problem types and owning a project from problem definition through modeling and evaluation, rather than specializing narrowly in one domain.
  • Core ML & statistics toolkit: regression and classification, tree-based ensembles (XGBoost/LightGBM/Random Forest), scorecard/GLM-style modeling, feature engineering, cross-validation, and rigorous model evaluation (AUC, KS, precision/recall, calibration).
  • Time-series and forecasting methods: classical approaches (ARIMA/exponential smoothing) as well as ML-based forecasting, with the judgment to choose the right method for the data and business question.
  • Strong data wrangling and cleaning skills: comfortable working with messy, incomplete, or inconsistent real-world data, building robust preprocessing pipelines, and validating data quality before it reaches a model.
  • Comfortable giving and receiving code review, and setting a bar for the rest of the team, not just meeting it.
  • Experience with a modern ML stack (Python, SQL, common ML/DL frameworks) - specific cloud provider experience is not required.
  • Bachelor's degree in Computer Science, Statistics, Engineering, or a related quantitative field required; Master's a plus
  • 3-5 years of proven experience as a Data Analyst or Data Scientist and
  • Experience with database and model design and segmentation techniques
  • Ownership
  • Functional Skills
  • Ideas presentation and Taking initiative
  • Continuous Learning
  • Customer Centricity
  • Familiarity with Big Data Echo systems
  • General knowledge regarding Data management and Governance
  • Fluent in Spark coding
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