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Associate Data Analyst
Job Location:
Monthly Salary:
Experience Required:
Posted:
24 May 2026 (30+ days ago)
Posted:
Application Deadline:
21 August 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
About Sproxil
Sproxil is a global technology company delivering trusted data product authentication and market intelligence across healthcare and consumer goods. Operating across Africa Asia and the Americas Sproxil partners with multinational brands donor agencies governments and NGOs to deploy mobile-technology solutions that combat counterfeiting drive consumer engagement and strengthen supply chain integrity. Sproxil is ISO 9001 and ISO 27001 certified and proudly serves over 200 global brands across ten industries.
Role Summary
The Associate Data Analyst will support Sproxils Analytics & Data Intelligence team in turning large volumes of product verification consumer engagement supply chain and public health data into actionable insights. Working directly under the Lead Data Analyst the role holder will assist in the full data analysis lifecycle from data acquisition and cleaning to dashboard development and reporting across Sproxils diverse client programmes in pharmaceuticals FMCG cosmetics agribusiness and donor-funded public health initiatives.
Key Responsibilities
Apply descriptive and inferential statistical methods to extract meaningful findings from surveys and public health datasets.
Conduct hypothesis testing regression analysis and significance testing to validate trends and support evidence-based decision-making.
Collect clean validate and organise data from multiple internal and external sources including Sproxils authentication platform call centre systems CRM field surveys and client datasets.
Conduct exploratory data analysis to uncover trends patterns and anomalies across product verification volumes consumer behaviour supply chain activity and campaign performance.
Develop and maintain dashboards and automated reports using Power BI Tableau or similar tools to communicate key metrics to internal teams and clients.
Support the Lead Data Analyst in preparing data-driven insight reports presentations and periodic client performance reviews.
Write SQL queries to extract transform and load data from PostgreSQL and other relational databases used across Sproxils technology stack.
Assist in the design and implementation of data quality frameworks ensuring accuracy completeness and consistency of data across all pipelines.
Support the analysis of CATI (Computer-Assisted Telephone Interview) survey data and field operations data for programme evaluation and reporting.
Sproxil Nigeria Limited Confidential Page
Collaborate cross-functionally with product engineering service delivery and business development teams to provide data support for decision-making.
Requirements
Qualifications & Experience
Bachelors degree or its equivalent in Statistics Epidemiology Public Health Biostatistics Mathematics Computer Science or a related quantitative field.
Minimum 2 years of hands-on experience in a data analyst or quantitative research role. Demonstrable exposure to public health or health programme data environments is an added advantage
Proven practical experience in data modelling preferable statistical predictive or epidemiological models applied to real-world public health datasets (e.g. disease surveillance HMIS data programme evaluations).
Proficiency in SQL for data extraction and manipulation (PostgreSQL experience preferred).
Working knowledge of Python or R for data wrangling analysis and basic visualisation (Pandas NumPy Matplotlib or equivalent).
Experience with Power BI at least one other BI/visualisation tool Tableau Google Looker Studio or similar.
Solid understanding of data cleaning transformation and quality assurance principles.
Familiarity with Microsoft Excel for data analysis including pivot tables VLOOKUP and basic statistical functions.
Nice to Have
Exposure to machine learning concepts or predictive modelling.
Experience working with supply chain consumer engagement or public health datasets.
Knowledge of data pipeline tools or ETL processes.
Familiarity with Git or version control for analytical projects.
Core Competencies
Analytical Thinking
Ability to break down complex data problems and draw meaningful conclusions
Attention to Detail
High accuracy in data work especially in quality-managed client-facing environments
Communication
Presents data insights clearly in written reports dashboards and verbal briefings
Collaboration
Works effectively with cross-functional teams across engineering product and field operations
Initiative & Curiosity
Proactively seeks new ways to add value through data; keeps up with industry developments
Sproxil Nigeria Limited Confidential Page
Sproxil is an equal opportunity employer. The above statements describe the general nature and level of work to be performed and should not be construed as an exhaustive list of all responsibilities. All employees may be required to take on additional responsibilities from time to time.
Benefits
Work-life balance (Hybrid)
13th month Salary
HMO
Competitive salary
Reward & Recognition
Required Skills:
Proven practical experience in data modelling preferable statistical predictive or epidemiological models applied to real-world public health datasets (e.g. disease surveillance HMIS data programme evaluations). Proficiency in SQL for data extraction and manipulation (PostgreSQL experience preferred). Working knowledge of Python or R for data wrangling analysis and basic visualisation (Pandas NumPy Matplotlib or equivalent). Experience with Power BI at least one other BI/visualisation tool Tableau Google Looker Studio or similar. Solid understanding of data cleaning transformation and quality assurance principles. Familiarity with Microsoft Excel for data analysis including pivot tables VLOOKUP and basic statistical functions.
Required Education:
Bachelors degree or its equivalent in Statistics Epidemiology Public Health Biostatistics Mathematics Computer Science or a related quantitative field. Minimum 2 years of hands-on experience in a data analyst or quantitative research role. Demonstrable exposure to public health or health programme data environments is an added advantage
