Data Analyst Job AutoXpress

We operate in a data-rich environment, with many complex datasets covering our customers, transactions, financials, marketing activities, workshops and many more. As we continue to expand, we are looking for a talented analyst to join our team. We are looking for someone who can use data to generate actionable insights to improve business outcomes (e.g., customer satisfaction, profitability, ROI of marketing campaigns).

This position is based in Nairobi, Kenya.

An overview of the duties and responsibilities of the role are outlined below:

a) 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
c) Reporting:

Develop visually compelling data visualizations and reports to convey insights to non-technical stakeholders.
Be able to generate and distribute reports, dashboards, and key performance indicators (KPIs) to relevant stakeholders.
Qualifications

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.