Senior Data Analyst at Unifi Group

Requirements

• Bachelor's or master's degree in a relevant field (e.g., Mathematics, Statistics, Computer Science, Data Analytics/Science).
• Proven experience as a Data Analyst or similar role win min experience of 6+ years
• Proficiency in data analysis tools GCP (Google Cloud Platform), Google Big Query, SAS, SQL, Python, R and data visualization tools Google Looker.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Ability to handle and analyse large datasets efficiently.
• Experience with statistical analysis techniques and data modelling.
• Excellent communication and presentation skills.
• Proficiency in Microsoft Excel and other data manipulation tools.
• Familiarity with data governance principles and best practices.
• Knowledge of data privacy regulations and compliance standards is a plus.
• Ability to travel occasionally across Africa

Duties and Responsibilities

Data Collection and Cleaning:

• Collect, extract, and compile data from various sources, ensuring data accuracy and completeness.
• Clean and transform raw data into structured datasets for analysis.
• Identify and resolve data quality issues, inconsistencies, and anomalies.
• Utilizing the technologies of SQL, SAS, Python and Big Query, while staying up-to-date with latest trends and developments in data analytics. 

Data Analysis and Interpretation:

• Perform exploratory data analysis to identify trends, patterns, and relationships within the data.
• Apply statistical techniques and data visualization methods to interpret and present findings.
• Analyse large and complex datasets to derive actionable insights and recommendations.
• Collaborate with stakeholders to understand business requirements and translate them into analytical approaches.

Reporting and Visualization:

• Create visualizations, dashboards, and reports to effectively communicate data insights to stakeholders with help of Google Looker.
• Develop and maintain standardized reporting templates and data visualization tools.
• Present findings in a clear and concise manner, tailoring the information to the audience's needs.

Data-driven Decision Making:

• Collaborate with cross-functional teams to support data-driven decision-making processes.
• Provide analytical support for business initiatives, including market analysis, customer segmentation, and performance tracking.
• Identify opportunities for process improvement, operational efficiencies, and revenue optimization based on data analysis.

Data Governance and Security:

• Ensure compliance with data governance policies, data protection regulations, and security protocols.
• Adhere to data privacy and confidentiality standards when handling sensitive information.
• Contribute to the development and maintenance of data dictionaries and data documentation.

Continuous Learning and Development:

• Stay updated with industry trends, best practices, and emerging technologies in data analysis.
• Expand knowledge of statistical analysis techniques, data modelling, and data visualization tools.
• Participate in training programs, workshops, and professional development opportunities.