You may be wondering…Data Analytics vs Data Science Salary in Nigeria, which one pays more in Nigeria.
As Nigeria’s economy steadily embraces digital transformation with growing fintech, e-commerce, telecom, and analytics-focused firms demand for data-savvy professionals remains high.
If you’re considering a career in data, one compelling question often arises: How do salaries compare between data analytics and data science roles in Nigeria?
This article unpacks current salary trends (2025/2026), typical ranges for different experience levels, and the factors affecting pay.
It will also provide a practical comparison between the two career paths, helping students, early-career professionals, or career switchers decide which might be more financially rewarding for them.
What Do We Mean by Data Analytics vs Data Science Salary
Data Analytics?
Data analytics broadly refers to collecting, cleaning, interpreting, and visualizing existing data to help organisations make business decisions.
Data analysts often use tools such as Excel, SQL, Power BI, Tableau…sometimes supplemented with scripting (Python/R) for automation or advanced analysis.
Data Science
Data science expands on analytics by applying statistical methods, machine learning, predictive modelling, and algorithmic thinking to extract deeper insights.
Data scientists might build predictive models, run experiments, clean large datasets, and often require programming proficiency (e.g. Python, R), as well as knowledge of ML frameworks, data pipelines, and sometimes domain-specific algorithms.
Because of this added complexity and demand for more technical skills, data science roles generally command higher salaries on average.
SEE ALSO: 10+ Best Data Analysis Training in Lekki 2026
Data Analytics vs Data Science Salary Overview in Nigeria 2026
While there’s no universal “standard salary,” a number of surveys and job-market analyses help us create a realistic picture.
Across various sources, the ranges vary depending on experience, industry, skills, location (Lagos, Abuja, Port Harcourt tend to pay more), and employer type (startup, corporate, multinational).
Data Analytics / Data Analyst Salary
According to a 2025 report by a Nigerian data-analysis association: entry-level data analysts (0–2 years) typically earn ₦150,000 – ₦350,000/month. Junior to mid-level (2–4 years) might get ₦350,000 – ₦700,000/month, while senior analysts (5+ years) can reach ₦700,000 – ₦1,500,000+/month depending on the role and responsibilities.
A recent breakdown based on actual job postings shows mid-range analysts earning about ₦236,667/month (as of Aug 2024).
Another summary suggests that, with progression and the right skills (e.g. BI tools, SQL, Python), salaries can scale higher especially in Lagos or other major cities.
In short, a data analyst with several years of experience and solid skills can potentially earn a very respectable salary in Nigeria’s major economic hubs.
Data Science / Data Scientist Salary
Because of the specialized, technical nature of data science, salaries tend to skew higher than analytics.
A 2025 survey estimates the average monthly salary for data scientists around ₦516,958/month, with reported ranges from about ₦248,075 to ₦811,292/month, depending on experience and role complexity.
Using a 2025 online salary-compilation source, many data scientists report total compensation (base + bonus/stock/benefits) in the ballpark of ₦6.08 million per year (≈ ₦506,700/month), though this can vary widely depending on company, seniority, and contract specifics.
In practice, entry-level or less-experienced data scientists might earn on the lower end but mid-level to senior data scientists, especially in industries like fintech or telecom, tend to command better pay because of demand for ML, predictive analytics, and data-driven decision support.
Data Analytics vs Data Science Salary: Side-by-Side Comparison
| Aspect | Data Analytics | Data Science |
|---|---|---|
| Entry-level Monthly Pay (approx.) | ₦150,000 – ₦350,000 | ~₦250,000 – ₦330,000 |
| Mid-level / Experienced Monthly Pay | ₦350,000 – ₦700,000 (could go higher with BI, Excel + SQL + basic Python/R) | ₦500,000 – ₦700,000+ (with ML/stats skills) |
| Senior / Specialist Roles | ₦700,000 – ₦1,500,000+ depending on responsibility, company, and tools used | ₦800,000 – ₦2,000,000+ (especially with advanced modelling, leadership, or niche skills) per broader market data. |
| Demand & Growth Potential | Strong demand across many sectors like retail, fintech, telecom, healthcare, start-ups; especially for clean data-driven insights. | Growing rapidly; companies investing in predictive analytics, ML, and data-driven modelling prefer data scientists; demand is especially high in fintech, telecom, tech start-ups. |
| Skill & Responsibility Scope | Data cleaning, reporting, dashboards, business intelligence, basic scripting. | Advanced data processing, statistical analysis, predictive models, machine learning, experimentation, potentially data engineering + ML pipelines. |
| Typical Employers / Industries | Banks, retail companies, consulting firms, e-commerce, SMEs, NGOs. | Fintech, banks, telecom, e-commerce, large tech startups, companies pursuing AI/ML initiatives. |
SEE ALSO: 10+ Best Places Where to Learn Data Analysis in Surulere 2026
Why Data Science Typically Pays More
Higher Technical Complexity: Data science often requires strong programming (Python, R), statistics, machine learning, and sometimes infrastructure skills that are scarce and demand premium pay.
Impact on Business Outcomes: The insights derived from models (e.g. customer churn predictions, risk assessment, demand forecasting) directly influence strategic decisions; hence, companies are willing to pay more.
Talent Scarcity: There are fewer professionals with genuine data-science skill sets (as opposed to basic analytics), especially within Nigeria; scarcity drives up value.
Career Progression & Leadership Opportunities: Data scientists often evolve into ML engineers, data science leads, or heads of analytics roles that carry higher compensation and responsibilities.
When Data Analytics Might Be the Better Choice (Even With Lower Pay)
Choosing between analytics and data science should not be solely based on salary. Here are valid reasons why data analytics could be a smart, even preferable, choice:
- Lower Barrier to Entry: Basic analytics tools (Excel, SQL, BI dashboards) are easier to learn; you may start a career without needing deep programming or statistical background.
- Stable Demand Across Many Sectors: Virtually every company needs someone to interpret their data from SMEs to large firms. Analytics skills remain evergreen.
- Faster Entry into the Workforce: You can begin earning relatively quickly and build experience, especially if you master Excel, SQL, and a BI tool.
- Work–Life Balance & Less Technical Overhead: Analytics roles may involve less pressure than heavy model-building or ML-pipeline maintenance; sometimes less stress and more predictable work.
Key Factors in 2026 That Will Shape Salaries
As we enter 2026, several macro and micro factors will influence how salaries evolve in Nigeria’s data analytics and data science fields:
- Industry Growth in Fintech, Telecoms, E-commerce, Healthcare: As companies gather more data and demand deeper insights, analytics and data science roles will remain in high demand.
- Adoption of Machine Learning & AI: Firms increasingly explore ML/AI for business advantage. This raises demand (and pay) for data scientists, ML engineers, and people with advanced skill sets.
- Remote Work & Global Gig Economy: Nigerian professionals who can deliver remotely (for global firms or clients) may command significantly higher pay, often in foreign currency raising earning potential beyond local market standards.
- Skill Specialization: Possessing specialized skills (ML, deep learning, big data, cloud computing, advanced statistics) will differentiate professionals and potentially double or triple earning potential compared to generalists.
- Location & Company Size: Opportunities in Lagos, Abuja, and other commercial hubs will likely continue to offer better packages than smaller towns; multinational or large firms will pay more.
SEE ALSO: 10+ Best Places Where to Learn Data Analysis in Surulere 2026
Which Career Path Should You Choose? (Analytics or Science?)
The “right” path depends on your interests, background, and career goals. Use the decision guidance below:
- Pick Data Analytics if you are just starting out, have limited coding or statistical background, want quicker entry into the job market, or want a more stable and broadly applicable skill set.
- Pick Data Science if you enjoy programming, statistical modelling, and want to build predictive/algorithmic solutions; also ideal if you aim for higher earning potential and are comfortable with continuous learning and technical complexity.
- Hybrid Approach: Many professionals begin in analytics, build a solid foundation, then upskill (learn Python/R, basic ML) to transition into data science. This allows gradual growth while gaining real-world context.
- Long-term Goals: If you aim to lead analytics teams, build ML-driven products, or work in high-impact sectors (fintech, e-commerce, telecom), data science gives more upward mobility.
Tips to Maximise Salary (Whether Analytics or Science)
- Build Strong Core Skills: For analytics, master SQL, Excel, one BI tool (Power BI, Tableau). For science, add Python/R, statistics, ML basics.
- Get Certified or Build Portfolio: Certifications or real-world projects (dashboards, data visualization, small ML projects) help. Employers value demonstrable skills.
- Target High-paying Industries & Locations: Fintech, telecom, oil & gas, large corporates; role in major cities (like Lagos) tends to pay more.
- Negotiate & Monitor Market Rates: Use salary surveys and market data to benchmark; when negotiating, highlight skills, impact, and demand.
- Stay Updated & Upskill: Data tools evolve fast, keep learning (new BI tools, ML libraries, cloud data pipelines) to stay relevant and increase value.
Conclusion on Data Analytics vs Data Science Salary in Nigeria
When comparing Data Analytics vs Data Science Salary in Nigeria, the data favors data science for higher earning potential especially for mid- to senior-level roles with strong technical skills.
However, data analytics remains a solid, accessible, and widely needed career path, ideal for many, particularly at entry-level or early career.
Ultimately, the best choice depends on your interests, willingness to learn, and long-term professional goals.
Many have successfully begun in analytics and migrated into data science over time.
With Nigeria’s growing data-driven economy, both paths remain viable, rewarding, and promising in 2026.
