The role of the Data Analyst at AutoXpress Ltd is critical in leveraging the company's complex, data-rich environment (covering customers, transactions, financials, marketing activities, workshops, and many more) to generate actionable insights. The objective of this position is to improve overall business outcomes, such as customer satisfaction, profitability, and the ROI of marketing campaigns. This position is based in Nairobi, Kenya.
Duties and Responsibilities
Data Collection and Preparation:
- Data Gathering: Collect, organize, and clean data from various sources, including databases, spreadsheets, and external data sets.
- Data Validation: Ensure data accuracy, consistency, and completeness by performing validation checks and data cleaning as needed.
- Data Integration: Integrate data from different sources to create comprehensive datasets for analysis.
Data Analysis and Insights:
- Analysis Planning: Work with stakeholders to define the objectives of data analysis and create analysis plans.
- Statistical Analysis: Apply statistical techniques to analyze data, identify trends, and draw meaningful conclusions.
- Trend Identification: Identify patterns and trends within the data that can inform business decisions.
- Predictive Modelling: Build and implement predictive models to forecast future trends or outcomes.
- Actionable insights: Use analysis to generate actionable insights that can improve business outcomes and decision making.
Reporting:
- Develop visually compelling data visualizations and reports to convey insights to non-technical stakeholders.
- Generate and distribute reports, dashboards, and key performance indicators (KPIs) to relevant stakeholders.
Qualifications & Experience
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
- Minimum 3 years of experience as a Data Analyst or in a similar role.
- Proficiency in data analysis tools such as SQL, Python, R, Excel, etc.
- Strong analytical and problem-solving skills.
- Excellent communication and presentation abilities.
- Ability to work with large datasets and derive meaningful conclusions.
- Attention to detail and a proactive mindset towards data analysis.
- Experience with data visualization tools is a plus.
