Data Analyst at CLS Human Capital Specialists

About the Role:

• A company based in Brooklyn, Pretoria is seeking a motivated and detail-oriented Data Analyst to join their team. The ideal candidate will have a strong foundation in data analysis, with the ability to derive insights from complex data sets to drive business decisions. This role requires an analytical mindset and proficiency in data manipulation and visualisation tools.

Requirements:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• Minimum of 3 years of experience in a data analysis role.
• Proficiency in SQL and experience with relational databases.
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Strong analytical skills with the ability to collect, organise, analyse, and disseminate significant amounts of information with attention to detail and accuracy.
• Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc.).
• Excellent communication and collaboration skills to effectively share findings and work across departments.
• Ability to handle multiple projects simultaneously in a fast-paced environment.

Preferred Experience:

• Experience with Python or R for data analysis.
• Knowledge of machine learning techniques and their real-world advantages/drawbacks.
• Experience in an industry-specific role, providing contextually relevant insights.

Key Responsibilities:

• Collect, process, and clean data from various sources to ensure accuracy and completeness.
• Analyse large datasets to identify trends, patterns, and correlations that can impact business decisions.
• Develop and maintain dashboards and reports using data visualization tools to present actionable insights to stakeholders.
• Collaborate with cross-functional teams, including marketing, sales, and product development, to support company objectives.
• Conduct ad hoc analyses to address specific business questions and provide comprehensive conclusions.
• Assist in the development and implementation of data collection systems and other strategies that optimize data quality and efficiency.
• Proactively identify opportunities for data-driven improvements and recommend actions to stakeholders.