Junior Data Analyst

Asharq News

Key Responsibilities:

• Collect, clean, and validate data from multiple sources (databases, spreadsheets, APIs, analytics tools).
• Run exploratory data analysis to identify trends, outliers, correlations and patterns.
• Build and maintain dashboards and reports using tools like Power BI, Tableau, Looker Studio, or Excel.
• Generate recurring and ad-hoc performance reports for business stakeholders.
• Assist in developing KPIs, metrics, and automated reporting solutions.
• Support senior analysts with deeper analyses, modeling, and data interpretation.
• Support predictive analysis tasks such as trend forecasting and segmentation under supervision.
• Work with senior team members to prepare datasets for machine learning workflows (feature preparation, labelling, dataset structuring).
• Document data processes, definitions, and workflows.
• Ensure data accuracy and consistency across internal systems.
• Collaborate with cross-functional teams such as product, Editorial, Digital, marketing and content.
• Present insights in a clear, concise manner to non-technical teams.

Qualifications & Experience:
Bachelor s or Master s (preferably in Data Science, Statistics, Computer Science, Business Analytics, Economics, or a related field)
3+ years of experience in analytics roles within media, entertainment, Tech, or digital ecosystems.

• Strong analytical and problem-solving abilities.
• Proficiency in Excel (pivot tables, formulas, data cleaning, visualizations).
• Foundational knowledge of SQL for data extraction and querying.
• Familiarity with BI tools (Power BI, Tableau, Looker Studio).
• Basic understanding of Python for data analysis (Pandas, NumPy, basic visualizations).
• Understanding of data science fundamentals such as:
• Descriptive statistics
• Correlation & regression basics
• Hypothesis testing
• Introductory machine learning concepts
• Ability to work with large datasets with strong attention to detail.
• Clear communication skills.
• Experience with cloud platforms (BigQuery, Snowflake, AWS, Azure).
• Exposure to predictive models, clustering, or classification tasks.
• Basic knowledge of data pipelines / ETL and workflow tools.
• Familiarity with digital analytics tools (GA4, Firebase, Adobe Analytics).

Understanding of version control (Git/GitHub).