Job Role: Data Analyst / Data Scientist (Big Data)
Location: Riyadh , Saudi Arabia
Job Mode : Onsite
Job Type : Contract
Job Summary:
We are seeking a Data Analyst / Data Scientist with strong big data experience to analyze large
heterogeneous datasets, build statistical and ML models, and deliver actionable insights and dashboards. The role emphasizes analytics, modeling, and stakeholder-facing reporting while collaborating with data engineers for data access and pipeline needs.
Key Responsibilities
- Analyze large-scale datasets to identify trends, drivers, anomalies, and business opportunities.
- Design, develop, validate, and deploy statistical models and machine-learning solutions to solve business and clinical problems.
- Prepare, clean, transform, and model data for analysis in collaboration with data engineering teams.
- Build interactive dashboards, visualizations, and automated reports to support decision-making.
- Conduct exploratory data analysis, A/B testing, cohort analyses, and predictive analytics.
- Translate analytical findings into clear, actionable recommendations and present to stakeholders.
- Ensure reproducibility by maintaining notebooks, pipelines, model artifacts, and documentation.
- Implement monitoring for model performance and work with engineers to operationalize models.
- Uphold data governance, privacy, and security standards for sensitive healthcare data.
Qualification and Experience
- Bachelor’s or Master’s in Data Science, Statistics, Computer Science, Engineering, or related field.
- 5+ years of experience in data analysis, applied statistics, or data science on large datasets.
- Experience working with healthcare data is preferred.
Technical Skills
- Strong SQL and Python; R acceptable.
- Experience with big data frameworks and querying large datasets.
- Familiarity with data engineering tools (Azure Data Factory, ETL concepts) to collaborate effectively.
- Experience building dashboards in Power BI or Tableau.
- Experience with model validation, feature engineering, and ML lifecycle (training, evaluation, deployment).
- Knowledge of statistical testing, regression, time-series, clustering, and classification techniques.
Work Location: In person
