Machine Learning Engineer

About the Role
In this position, 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, utilizing Python and Dataiku for the models and Qlik, Power BI, and Python for the visuals. This role covers both the data-science and analysis side of the project as well as the business intelligence aspects.

What You Will Do

• Qualify and prioritize use cases with the client, then build, deploy, and monitor the models.
• Perform statistical analysis behind each use case and explain the results to non-technical stakeholders.
• Design and build dashboards and automated reports in both Arabic and English.
• Conduct training on masked or de-identified data, while documenting the features and data used.
• Maintain the health of models and dashboards, including retraining, drift monitoring, scheduled refreshes, and performance tracking.
• Assist in writing the monthly progress report for AI and dashboard work.

What You Need

• Proficiency in the Python ML stack (pandas, scikit-learn, and either PyTorch, TensorFlow, or XGBoost) with experience running models in production.
• Experience in forecasting, segmentation, recommendation, and NLP use cases.
• Knowledge of MLOps, including reproducible training, deployment, monitoring, and retraining.
• Strong background in statistical analysis and experimental design.
• Expertise in Qlik Sense, including load scripts, associative models, set analysis, section access, and report automation.
• Proficiency in Power BI, including data modeling, DAX, Power Query, row-level security, and scheduled refresh.
• Experience with Python reporting and visualization tools (e.g., Plotly, Dash, Streamlit).
• Ability to design bilingual dashboards accommodating right-to-left text.
• Commitment to privacy-aware practices, including data masking and de-identification.

Good to Have

• Knowledge in Arabic NLP and experience with Vertex AI or BigQuery ML.
• Experience in marketing-mix, attribution, or uplift modeling.
• Relevant certifications in Qlik or Power BI; Google Professional Machine Learning Engineer certification.