16.10.2026 aktualisiert
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Data Analyst - SQL, Python, Power BI-Data Entry
Amman, Jordanien
Nur Remote
Bachelor of Science (BSc) in Physics, University of JordanÜber mich
Data Analyst with a Physics degree and hands-on experience in SQL, Python and Power BI. Skilled at turning ambiguous business questions into clear analytical problems, investigating unexpected results, and maintaining high standards of data quality and data integrity
Skills
Adobe AnalyticsSql Data WarehouseAnalyse von FinanzdatenBig DataBusiness AnalysisCodeanalyseData ArchitectureData ControlData IntegrationData Manipulation LanguageData MiningData-ProfilingDatenbankanalyseDatenbankabfragenDatenbank-Tests
Programming and Querying
Proficiency in SQL (Snowflake, MySQL, CTEs, window functions, joins, aggregation) and Python (Pandas, NumPy, Scikit-learn, XGBoost), as well as FastAPI for building data-driven applications.
Data Analysis and Statistics
Expertise in statistical analysis, regression modelling, classification, exploratory data analysis (EDA), cohort analysis, retention analysis, KPI development, data transformation, and ETL automation.
BI and Data Visualisation
Strong command of Power BI (DAX, data modelling, dashboards), advanced Excel, Jupyter dashboards, data visualisation, and stakeholder reporting.
Data Quality
Experience in data validation, data cleaning, data integrity checks, and root cause investigation of anomalies to ensure high standards of data accuracy.
Platforms and Tools
Hands-on experience with Microsoft Azure, Snowflake, Git, and GitHub for cloud-based data management and version control.
Machine Learning
Application of XGBoost and Random Forest classification models for fraud detection and anomaly detection, achieving measurable improvements in accuracy.
ETL Automation
Development of automated ETL pipelines to streamline data preprocessing and reduce processing time significantly.
Financial and Business Analytics
Conducting SQL and Python analysis of public-company revenue growth, profit margins, cash flow, ROE, and debt ratios, delivered as executive Jupyter dashboards.
Proficiency in SQL (Snowflake, MySQL, CTEs, window functions, joins, aggregation) and Python (Pandas, NumPy, Scikit-learn, XGBoost), as well as FastAPI for building data-driven applications.
Data Analysis and Statistics
Expertise in statistical analysis, regression modelling, classification, exploratory data analysis (EDA), cohort analysis, retention analysis, KPI development, data transformation, and ETL automation.
BI and Data Visualisation
Strong command of Power BI (DAX, data modelling, dashboards), advanced Excel, Jupyter dashboards, data visualisation, and stakeholder reporting.
Data Quality
Experience in data validation, data cleaning, data integrity checks, and root cause investigation of anomalies to ensure high standards of data accuracy.
Platforms and Tools
Hands-on experience with Microsoft Azure, Snowflake, Git, and GitHub for cloud-based data management and version control.
Machine Learning
Application of XGBoost and Random Forest classification models for fraud detection and anomaly detection, achieving measurable improvements in accuracy.
ETL Automation
Development of automated ETL pipelines to streamline data preprocessing and reduce processing time significantly.
Financial and Business Analytics
Conducting SQL and Python analysis of public-company revenue growth, profit margins, cash flow, ROE, and debt ratios, delivered as executive Jupyter dashboards.
Erfahrung
Berufserfahrung0 - 5 Jahre
Freelancer seit2025
Sprachen
ArabicMutterspracheEnglishMuttersprache
Projekthistorie
End-to-end analytics pipeline on 30,000 orders (about 52,000 line items) from 5,000 customers. SQL analysis of revenue trends, customer cohort retention and category performance using CTEs and window functions (RANK, LAG, PARTITION BY); published on GitHub.
Power BI dashboard on a deliberately messy 1,225-record logistics dataset: data cleaning, on-time delivery rate, carrier and warehouse analysis.
Entered and maintained student, staff and administrative records with a focus on data accuracy and consistency.