Bachelor of Science (Any, Computers), Bachelor of Arts (Statistics)
Nationality
Any Nationality
Vacancy
1 Vacancy
Job Description
Position Objectives
- Prepare high-quality data for machine learning pipelines to ensure robust model performance.
- Support model evaluation, visualization, and validation processes to drive reliable outcomes.
- Apply explainability techniques and deliver actionable insights through effective reporting.
Job Description & Responsibilities
- Conduct data exploration, profiling, cleaning, and feature extraction to build robust datasets.
- Implement explainability tools (e.g., SHAP, LIME) to enhance model transparency and interpretability.
- Collaborate with cross-functional teams on experimentation, model validation, and iterative improvements.
- Assist in integrating BI tools (e.g., Power BI) and craft compelling data storytelling for stakeholders.
- Establish and maintain clean, efficient data pipelines to support scalable ML workflows.
- Deliver validated models quarterly, meeting performance and reliability standards.
- Ensure stakeholder satisfaction through clear, impactful reports and actionable insights.
- Customer/Stakeholder Focus: Build usable AI solutions tailored to stakeholder needs.
- Presentation Skills: Lead demos, share insights, and conduct architecture walkthroughs.
Qualifications & Experience
- Bachelor's or master's degree in Statistics, Computer Science, Data Science, Mathematics, or Engineering.
- Minimum 8 years of experience as a Data Scientist.
- Hands-on experience as a lead, capable of formulating strategies, developing technical roadmaps, acting as a technical consultant, and implementing solutions.
- Expertise in Python (pandas, matplotlib), SQL, and machine learning frameworks.
- Experience with data storage, data modeling, and ETL processes.
- Knowledge of low-latency systems, storage optimization, and high-performance computing.
- Understanding of concepts used in OpenShift AI platforms.
- Familiarity with BI dashboards (e.g., Power BI) and data visualization.
- Soft Skills:
- Excellent communication skills in English (mandatory), Arabic (preferred).
- Strong collaboration and teamwork skills across AI, MLOps, Data, and Application teams.
- Problem-solving ability for debugging models and optimizing pipelines.
- Adaptability to evolving tools, frameworks, and use cases.
- Effective time management to meet deadlines for prototypes, deployments, and iterations.
- Keywords: Data Science, ML Support, Explainability, Feature Engineering, ETL, Data Storage, Storytelling, Insight Delivery, Business Empathy.
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