We are seeking a Data Analyst with a passion for unraveling insights from diverse data sets. The ideal candidate will possess strong statistical modeling skills and be proficient in managing, manipulating, and visualizing data sourced from unstructured formats (such as Google Sheets), along with structured data from data warehouses, with BI visualization tools. This role requires collaboration with cross-functional teams and occasional fieldwork in Tanzania.

Responsibilities:

• ●  Data Collection and Management:
  • ○  Collect and curate data from various sources, including but not limited to Google

    Sheets, databases, and APIs.

  • ○  Organize, clean, and maintain datasets to ensure data integrity and accessibility.
• ●  Statistical Analysis and Modeling:
  • ○  Apply statistical methods to interpret data trends and patterns.
  • ○  Develop and execute statistical models to derive actionable insights.
  • ○  Provide answers and context required for operational and strategic

    decision-making by the senior team.

• ●  Data Visualization:

○ Create visual representations (charts, graphs, dashboards) to effectively communicate data-driven insights, including daily data dashboards for team leads and decision-making.

• ●  Collaboration and Support:
  • ○  Collaborate with teams to understand data requirements and provide analytical

    support.

  • ○  Assist in the design and implementation of data-driven strategies and solutions.
• ●  Quality Assurance:

○ Perform quality checks on data outputs and analyses to ensure accuracy.

Qualifications:

1. Bachelor's degree in a relevant field such as Statistics, Mathematics, or Computer Science.
2. Proficiency in data manipulation tools (e.g., SQL, Python, or R) and data visualization tools (e.g., Tableau, Power BI).
3. Strong attention to detail and ability to work with large datasets.
4. Excellent communication skills to convey complex findings to non-technical

   stakeholders.

5. Problem-solving mindset and ability to think critically about business challenges.
6. Familiarity with sales metrics, KPIs, and performance indicators.
7. Stay informed about industry best practices and emerging trends in data analysis.

Preferred Skills:

1. Experience with machine learning techniques for predictive analytics. 2. Knowledge of CRM systems and their data structures.
3. Understanding of statistical concepts and hypothesis testing.