Data Analyst

Vendorcredit

Job Overview

Location

Lagos, Lagos, Nigeria

Employment Type

Full-time

Work Arrangement

On-site

Sector

Information Technology & Software

Experience Level

Mid-level (3-5 years)

Application Deadline

September 4, 2026

About the Company

Vendorcredit is a dynamic player in the FinTech space, dedicated to providing innovative financial solutions. The company operates within the vibrant Lagos ecosystem, contributing to the digital transformation of financial services in Nigeria. Vendorcredit focuses on leveraging technology to enhance lending processes, making them more efficient and accessible. Their commitment to data-driven strategies ensures that they remain at the forefront of the industry, constantly adapting to market needs and client demands. The company fosters a culture of innovation and analytical rigor, empowering its team to explore new possibilities and deliver exceptional value.

Job Description

Vendorcredit is seeking a skilled Data Analyst to join their growing team in Lagos. This role is crucial for driving informed business decisions through insightful data analysis.

In this position, you will be responsible for collecting, cleaning, and analyzing complex datasets to identify trends, anomalies, and opportunities. You will translate data into actionable business insights and present your findings to stakeholders.

Your expertise will be vital in supporting the company's strategic objectives and enhancing its operational efficiency within the FinTech landscape.

To apply for this role, click the Apply button on this page and follow the instructions.

Required Skills

Microsoft ExcelSQLPower BITableauLookerPythonRRelational DatabasesETL ProcessesData WarehousingAPIsData IntegrationStatistical AnalysisAnalytical ThinkingProblem-SolvingCritical ThinkingData VisualizationCommunicationPresentation SkillsAttention to Detail

Key Responsibilities

Collect, clean, and analyze financial, transactional, or lending datasets.
Develop and implement advanced analytical models using Python or R.
Utilize SQL for data extraction and manipulation from relational databases.
Create compelling data visualizations and dashboards using Power BI, Tableau, or Looker.
Identify trends, anomalies, and business opportunities from data.
Convert complex data into meaningful business insights and recommendations.
Collaborate with cross-functional teams to understand data needs and deliver solutions.
Ensure data accuracy and integrity throughout the analysis process.
Communicate findings effectively through presentations and reports.
Integrate data from multiple sources using APIs and understand ETL processes.

Qualifications

Bachelor’s degree in Statistics, Computer Science, or a related quantitative discipline.
2–4 years of experience as a Data Analyst, preferably within a FinTech, Financial Services, Banking, or Technology environment.
Advanced Microsoft Excel and SQL skills.
Experience with Power BI, Tableau, or Looker.
Proficiency in Python or R for data analysis.
Strong understanding of relational databases.
Knowledge of ETL processes and data warehousing concepts.
Experience using APIs and integrating multiple data sources is an advantage.
Strong statistical and analytical thinking.
Ability to identify trends, anomalies, and business opportunities.
Excellent problem-solving and critical-thinking skills.
Ability to convert complex data into meaningful business insights.
Excellent communication and presentation skills.
Strong attention to detail and accuracy.

How to Apply

Click the application link below to apply.

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The financial technology sector in Lagos is experiencing rapid growth, driven by increasing digital adoption and demand for data-driven decision-making. This role is pivotal in leveraging vast datasets to uncover actionable insights that directly impact business ROI and strategic growth. You will be instrumental in developing robust analytical models, performing complex data mining, and implementing advanced statistical techniques. Your expertise in API integrations, ETL processes, and data warehousing will be crucial for optimizing data pipelines and ensuring data integrity, ultimately driving significant improvements in lending operations and customer engagement.