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.
