Data Scientist/Analyst - Data Modelling & BI | Emirati Talent

ROLE SUMMARY Provide data engineering, analytics, and dashboard development support to Majid Al Futtaim Global Solutions (MAF GS) by designing and optimizing data pipelines, creating insightful Tableau and Power BI dashboards, and delivering analytics and machine learning solutions that enhance data-driven decision-making and accelerate AI innovation initiatives.

ROLE PROFILE Design, develop, and optimize scalable data pipelines using Python and SQL/MySQL to ensure high-quality datasets are available for analytics and reporting. Build, enhance, and maintain interactive Tableau and Power BI dashboards, delivering actionable insights through clearly defined and governed KPIs.

Conduct exploratory data analysis and statistical assessments to identify trends, generate insights, and support operational and strategic decision-making. Develop and evaluate predictive analytics and machine learning models, leveraging tools such as scikit-learn to address business challenges and improve outcomes.

Create and deploy lightweight analytics applications and proof-of-concept solutions using Streamlit, improving stakeholder access to data and insights. Support AI, NLP, and Generative AI initiatives by contributing to experimentation, prototyping, and validation of innovative use cases.

Maintain comprehensive documentation for data models, dashboards, and code repositories while adhering to data quality, governance, and version control standards.

Deliver reporting-ready datasets, stakeholder-adopted dashboards, reusable analytical assets, and at least one analytics, ML, or AI prototype with documented outcomes and recommendations for future implementation.

REQUIREMENTS Proficiency in Python (Pandas, NumPy) and SQL/MySQL to manage, transform, analyze, and model data for business insights and reporting.

Strong expertise in data visualization and business intelligence tools, including Tableau, Power BI, and advanced Excel, with the ability to define and monitor meaningful KPIs.

Knowledge of exploratory data analysis, statistical techniques, and machine learning concepts, including feature engineering, model development, evaluation, and performance optimization.

Experience in developing and deploying analytics solutions and prototypes using Streamlit, with exposure to modern AI platforms and tools such as Hugging Face and NLP frameworks.

Familiarity with collaborative development environments and version control tools, including Git/GitHub, Jupyter/Colab, VS Code, and PyCharm, ensuring efficient project delivery and knowledge sharing.

Demonstrates strong analytical thinking, problem-solving ability, stakeholder communication, attention to detail, and a continuous learning mindset, supported by a relevant quantitative degree and practical experience through internships, academic project