Learning Experience Data Analyst Job Vacancy in Sapele, Nigeria – Education Technology

Job Description

Position:Learning Experience Data Analyst

Company:Pearson Nigeria

Location:Sapele, Nigeria

Experience:3-5 years

Education:Bachelor’s degree in Data Science, Statistics, Education, or related field

Employment Type:Full-time

Industry:Education Technology

Department:Data Analytics

Salary:₦2,500,000 – ₦3,500,000 per annum

Vacancies:1

Company Overview

Pearson Nigeria is a leading global education company dedicated to improving learning outcomes through innovative digital solutions. With a presence in over 70 countries, Pearson combines cutting‑edge technology, research‑backed content, and a deep understanding of local educational needs. In Nigeria, Pearson partners with schools, universities, and corporate training providers to deliver adaptive learning platforms, assessment tools, and professional development resources. The Sapele office serves as a strategic hub for the South‑South region, supporting a growing portfolio of e‑learning initiatives that empower teachers and learners alike. As part of Pearson’s commitment to talent development, the company fosters a culture of continuous improvement, collaboration, and data‑driven decision making, making it an ideal environment for professionals seeking to make a meaningful impact on education across Nigeria.

Job Overview

The Learning Experience Data Analyst will play a pivotal role in shaping Pearson’s digital learning products by translating complex data sets into actionable insights that enhance user engagement, learning outcomes, and product performance. Working closely with product managers, instructional designers, and engineering teams, you will analyze learner interaction data, assess the effectiveness of adaptive algorithms, and recommend data‑informed enhancements. This position offers a unique opportunity to contribute to the future of education technology in Nigeria while collaborating with an international team of experts. For more information about Pearson’s mission and current openings, visit Nigeria Job Search.

Key Responsibilities

• Collect, clean, and validate large volumes of learner interaction data from Pearson’s digital platforms.
• Perform exploratory data analysis to identify trends, patterns, and areas for improvement in learning pathways.
• Develop and maintain dashboards and visualizations that communicate key performance indicators to stakeholders.
• Collaborate with product managers to define metrics that align with business goals and educational standards.
• Conduct A/B testing and statistical analysis to evaluate the impact of new features or content updates.
• Provide actionable recommendations to instructional designers for optimizing content sequencing and difficulty levels.
• Support the engineering team by specifying data requirements for algorithm enhancements.
• Document analytical methodologies and ensure reproducibility of results.

Required Skills

• Proficiency in SQL, Python, or R for data manipulation and analysis.
• Experience with data visualization tools such as Tableau, Power BI, or Looker.
• Strong statistical knowledge, including hypothesis testing and regression analysis.
• Understanding of educational data, learning analytics, and adaptive learning concepts.
• Excellent communication skills to translate technical findings into clear business insights.
• Ability to work independently and collaboratively in a fast‑paced, cross‑functional environment.

Education

A bachelor’s degree in Data Science, Statistics, Computer Science, Education, or a related discipline is required. Advanced degrees or certifications in analytics, learning science, or educational technology are considered a strong advantage.

Experience

Candidates should have 3‑5 years of professional experience in data analysis, preferably within the education technology sector or a related field such as e‑learning, SaaS, or digital media. Prior experience working with learning management systems (LMS) or adaptive learning platforms is highly desirable.

Salary

The role offers a competitive annual salary ranging from ₦2,500,000 to ₦3,500,000, commensurate with experience and qualifications. Performance‑based bonuses and incentives may be awarded based on the impact of analytical contributions.

Benefits

• Health insurance covering medical, dental, and vision.
• Retirement savings plan with company matching.
• Generous paid time off and public holiday schedule.
• Professional development budget for certifications, conferences, and courses.
• Employee assistance program and wellness initiatives.

Training

• Comprehensive onboarding program covering Pearson’s products, data infrastructure, and compliance standards.
• Ongoing training in advanced analytics techniques, machine learning, and educational research methods.
• Mentorship opportunities with senior data scientists and instructional designers.

Working Environment

Pearson Nigeria promotes a flexible, inclusive workplace that values diversity of thought and background. The Sapele office offers modern workspaces, collaborative zones, and reliable high‑speed internet to support remote and hybrid work arrangements. Employees are encouraged to share ideas, experiment with new approaches, and contribute to a culture of innovation that drives educational excellence across Nigeria.

Application Process

Interested candidates should submit their updated resume and a cover letter outlining their relevant experience through the online portal on the Pearson careers page. Applications will be reviewed on a rolling basis, and shortlisted candidates will be invited to complete a data‑analysis case study followed by virtual interviews with the hiring team.

Equal Opportunity Statement

Pearson Nigeria is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, sexual orientation, or any other protected characteristic. All qualified applicants will receive consideration for employment without discrimination.