Data Analyst

Responsibilities of the Candidate:

• Collect, clean, validate, and analyze data from multiple sources.
• Write and optimize SQL queries to extract, transform, and manipulate data from relational databases.
• Perform statistical analysis using IBM SPSS, including regression analysis, hypothesis testing, ANOVA, clustering, and forecasting.
• Use Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data cleaning, exploratory data analysis (EDA), automation, and visualization.
• Develop dashboards, reports, and performance metrics for business stakeholders.
• Identify trends, patterns, anomalies, and actionable insights from large datasets.
• Collaborate with business teams to understand reporting and analytical requirements.
• Present findings and recommendations through reports, visualizations, and presentations.
• Ensure data quality, accuracy, and integrity across reporting processes.

Requirements:

• Strong SQL skills, including Joins, Subqueries, CTEs, Window Functions, and Aggregations.
• Knowledge of IBM SPSS for statistical analysis and modeling.
• Proficiency in Python, particularly Pandas, NumPy, Matplotlib, and Seaborn.
• Good understanding of statistics, data analysis, and data visualization.
• Knowledge of Excel and BI tools such as Power BI or Tableau is an advantage.
• Strong analytical, problem-solving, and communication skills.
• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Engineering, or a related field.
• Relevant certifications in Data Analytics, SQL, Python, or SPSS are a plus.