Machine Learning Engineer

About the Role
You will take machine-learning use cases from idea to production and build the dashboards and reports that decision-makers use every day. Expect around twenty use cases and twenty dashboards over the year, using Python and Dataiku for the models, and Qlik, Power BI, and Python for the visuals. This role encompasses both the data-science and analysis side of the project as well as Business Intelligence (BI).

What You Will Do

• Qualify and prioritize use cases with the client, then build, deploy, and monitor the models.
• Conduct the statistical analysis behind each use case and explain the results to those who are not technical.
• Design and build dashboards and automated reports in both Arabic and English.
• Train only on masked or de-identified data, and document the features and data you used.
• Maintain the health of models and dashboards: retraining, drift monitoring, scheduled refreshes, and performance.
• Contribute to the monthly progress report for AI and dashboard work.

What You Need

• Experience with the Python ML stack (pandas, scikit-learn, and one of PyTorch, TensorFlow, or XGBoost), with models you have actually run in production.
• Familiarity with forecasting, segmentation, recommendation, and NLP use cases.
• Knowledge of MLOps: reproducible training, deployment, monitoring, and retraining.
• Skills in statistical analysis and experiment design.
• Proficiency with Qlik Sense: load scripts, associative model, set analysis, section access, and report automation.
• Proficient in Power BI: data model, DAX, Power Query, row-level security, and scheduled refresh.
• Experience in Python reporting and visualization (using Plotly or Dash, Streamlit, or similar).
• Ability to design bilingual dashboards in a right-to-left format.
• Commitment to privacy-aware practices, including data masking and de-identification.

Good to Have

• Experience with Arabic NLP; familiarity with Vertex AI or BigQuery ML.
• Knowledge of marketing-mix, attribution, or uplift modeling.
• Certifications in Qlik or Power BI; Google Professional Machine Learning Engineer.