Data Scientist

The purpose of this role is to acquire, wrangle, analyze, and interpret data to derive actionable insights and drive strategic decision-making. The Data Scientist will apply advanced statistical modeling, machine learning, and data science methodologies to solve real-world business problems and optimize performance across the organization.

Key Responsibilities:

• Define and implement data collection strategies and pipelines to ensure high-quality, structured inputs for analysis.
• Perform data cleaning, transformation, and exploration on structured and unstructured data sources.
• Develop and deploy statistical models and machine learning algorithms to extract patterns and predict outcomes.
• Design and execute controlled experiments (A/B tests, multivariate tests) to evaluate business strategies and hypothesis-driven outcomes.
• Conduct feature engineering, apply advanced data preprocessing techniques, and evaluate various model configurations for performance improvement.
• Optimize hyperparameters (e.g., learning rate, number of layers, regularization) to fine-tune model performance.
• Develop and deploy machine learning pipelines for production environments.
• Perform fine-tuning of Large Language Models (LLMs) for custom use cases and business applications.
• Clearly communicate insights, analysis, and recommendations to technical and non-technical stakeholders.
• Stay current with cutting-edge research and apply new methodologies and tools in practical settings.
• Collaborate with cross-functional teams, including engineering, product, and business, to integrate data solutions.

Required Skills & Competencies:

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
• Solid foundation in Statistics, Probability, and Mathematical Modeling.
• Experience with Machine Learning, Deep Learning, and Data Mining techniques.
• Ability to perform data visualization using tools such as Matplotlib, Seaborn, Plotly, or Power BI/Tableau.
• Proficiency in data wrangling and data pipeline design (SQL, APIs, ETL tools).
• Strong analytical and problem-solving capabilities.
• Excellent communication skills—ability to explain complex ideas in simple terms.
• Proven experience in business-oriented data science—driving real-world impact.

Preferred Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
• Experience working with LLMs (e.g., GPT, BERT) and fine-tuning transformer-based models.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and ML Ops tools.
• Knowledge of data versioning, model monitoring, and deployment best practices.
• Background in business analytics or domain-specific problem-solving (finance, retail, healthcare, etc.).
• (Preferred but not required) Arabic-speaking capability to support regional teams.