At a glance
Data analyst and data scientist salary in Singapore
- Data analyst: S$5,869 median a month. Middle 50% earn S$4,561 to S$7,375.
- Data scientist: S$10,111 median, S$4,242 more than a data analyst.
- Data engineer: S$8,721 median.
- Graduates: S$5,000 for NUS Data Science and Analytics, S$5,700 for NUS Business Analytics.
- By employer: data analysts earn S$7,263 in information and communications, S$5,017 in transport and storage.
How does your pay compare?MOM figures, June 2025. Nothing you type leaves your browser.
Part 1 · Pay today
How much do data analysts and data scientists earn?
A data scientist earns S$10,111 at the median, S$4,242 more than a data analyst.
Gross monthly wage, June 2025, all industries.
| Occupation, all industries | Basic wage, median | Gross, 25th pct | Gross, median | Gross, 75th pct |
|---|---|---|---|---|
| Statistical officer/Data analystFull detail | 5,694 | 4,561 | 5,869 | 7,375 |
| StatisticianPartial detail | 7,723 | 6,292 | 7,723 | 9,173 |
| Data/Database administratorPartial detail | 8,115 | 5,750 | 8,471 | 13,540 |
| Data engineerPartial detail | 8,551 | 6,351 | 8,721 | 11,400 |
| Data scientistFull detail | 9,522 | 7,857 | 10,111 | 13,727 |
Source: MOM Occupational Wages 2025, Table 4. Full-time resident employees, June 2025.
Cell references
T4!C217:I217, T4!C218:I218, T4!C114:I114, T4!C112:I112, T4!C113:I113What it means
- MOM's data analyst title is statistical officer/data analyst. It covers reporting and analysis roles.
- Data scientist is a separate MOM title, usually for modelling and machine learning work.
- Data engineers earn S$8,721 and database administrators S$8,471.
Starting salary for data and analytics graduates
Data and analytics graduates earn S$4,550 to S$6,000 at the median six months after graduating.
Graduates in full-time permanent jobs, surveyed on 1 November 2025. These are the closest courses MOE reports.
| University and programme | Basic, median | Gross, median | Gross, mean | Gross, middle 50% |
|---|---|---|---|---|
| NUS, Data Science and Analytics | 5,000 | 5,000 | 5,380 | 4,450 to 6,000 |
| NUS, Business Analytics | 5,500 | 5,700 | 6,375 | 5,000 to 7,083 |
| SUSS, Business Analytics | 4,600 | 4,800 | 4,990 | 4,200 to 5,439 |
| NUS, Information Systems | 5,665 | 6,000 | 6,126 | 5,000 to 7,000 |
| SMU, Information Systems | 5,000 | 5,400 | 5,515 | 4,800 to 6,028 |
| SIT, Applied AI | 4,500 | 4,550 | 4,618 | 3,850 to 5,320 |
Full-time permanent jobs only, as at 1 November 2025. Source: MOE GES 2025 (NUS, SIT, SMU, SUSS).
What it means
- NUS Information Systems is highest at S$6,000, then NUS Business Analytics at S$5,700.
- NUS Data Science and Analytics graduates earn S$5,000.
- SIT Applied AI graduates earn S$4,550. NTU's Data Science and AI course has no 2025 figure.
Job outcomes for data graduates92.1% of responding NUS Information Systems graduates were in full-time permanent jobs, against 65.1% for NUS Data Science and Analytics.
92.1% of responding NUS Information Systems graduates were in full-time permanent jobs, against 65.1% for NUS Data Science and Analytics.
Share of graduates in the labour force.
| Programme | Course response rate | Currently employed | In full-time permanent employment |
|---|---|---|---|
| NUS, Data Science and Analytics | 72% | 75.2% | 65.1% |
| NUS, Business Analytics | 68% | 91.7% | 85.7% |
| SUSS, Business Analytics | 73% | 80.3% | 69.7% |
| NUS, Information Systems | 69% | 92.1% | 92.1% |
| SMU, Information Systems | 73% | 90.5% | 83.4% |
| SIT, Applied AI | 82% | 62.9% | 57.1% |
Share of graduates in the labour force. Source: MOE GES 2025.
What it means
- SIT Applied AI had the lowest rate in this group, 57.1%.
Part 2 · Who earns more
How pay changes with age
Data scientist pay rises from S$7,000 at 25 to 29 to S$13,186 at 50 to 59. Data analyst pay is highest in the thirties, at S$7,037.
Median gross monthly wage by age group.
Data scientistData analyst
| Occupation | 25–29 | 30–39 | 40–49 | 50–59 |
|---|---|---|---|---|
| Statistical officer/Data analyst | 5,833 | 7,037 | 5,846 | 5,552 |
| Data scientist | 7,000 | 9,693 | 11,154 | 13,186 |
| Data engineer | – | 8,726 | – | – |
| Data/Database administrator | – | 7,542 | 11,098 | – |
| Statistician | – | 7,243 | – | – |
Median gross monthly wage, S$. "–" = suppressed by MOM. Source: MOM Occupational Wages 2025, Table 3.
Cell references
T3!C187:K187, T3!C102:K102, T3!C101:K101, T3!C103:K103, T3!C188:K188What it means
- Data analysts aged 40 to 49 earn S$5,846, less than in their thirties. This may reflect experienced analysts moving to other titles.
- How to read it: each age band shows different people in June 2025, not one person's career.
By sex and employer sizeFemale data analysts earn S$6,400 at the median, more than male data analysts at S$5,620.
Female data analysts earn S$6,400 at the median, more than male data analysts at S$5,620.
| Occupation | All, median gross | Men | Women | Women vs men |
|---|---|---|---|---|
| Statistical officer/Data analyst | 5,869 | 5,620 | 6,400 | +13.9% |
| Data scientist | 10,111 | 10,595 | 9,537 | -10.0% |
| Data engineer | 8,721 | 9,010 | 7,036 | -21.9% |
| Data/Database administrator | 8,471 | 8,917 | 8,048 | -9.7% |
| Statistician | 7,723 | 8,075 | 7,594 | -6.0% |
Median gross monthly wage, S$. Two group medians, not an adjusted pay gap. Source: MOM Occupational Wages 2025, Tables 1.1 and 1.2.
Cell references
T1.1!C189:E189, T1.2!C186:E186, T1.1!C102:E102, T1.2!C104:E104, T1.1!C101:E101, T1.2!C103:E103, T1.1!C103:E103, T1.2!C105:E105, T1.1!C190:E190, T1.2!C187:E187| Occupation | Firms with 25 to 199 employees | Firms with 200 or more | Large vs small |
|---|---|---|---|
| Statistical officer/Data analyst | 6,300 | 5,844 | -7.2% |
| Data scientist | 11,158 | 10,027 | -10.1% |
| Data engineer | – | 8,726 | – |
| Data/Database administrator | 6,775 | 9,913 | +46.3% |
| Statistician | – | 7,723 | – |
Median gross monthly wage, S$. Source: MOM Occupational Wages 2025, Table 2.
Cell references
T2!C210:G210, T2!C113:G113, T2!C112:G112, T2!C114:G114, T2!C211:G211What it means
- Data scientists: S$10,595 for men and S$9,537 for women.
- Smaller firms pay data scientists more: S$11,158 at firms with 25 to 199 staff, against S$10,027 at larger firms.
- These compare two groups. They are not an adjusted pay gap.
By employer industry
Data analysts in information and communications earn S$7,263 at the median, against S$5,112 in manufacturing.
| Employer industry | Median gross wage | Gross wage, middle 50% |
|---|---|---|
| Information and Communications | 7,263 | 6,154 to 10,917 |
| Wholesale and Retail Trade | 7,262 | 6,100 to 9,501 |
| Financial and Insurance Services | 7,019 | 5,524 to 9,438 |
| Professional Services | 6,350 | 4,900 to 9,250 |
| Manufacturing | 5,112 | 4,220 to 6,387 |
| Transportation and Storage | 5,017 | 4,380 to 6,117 |
Statistical officer/Data analyst (SSOC 21231). Source: MOM Occupational Wages 2025, Tables 4.1 to 4.14. No figure published for the other 8 industries.
Cell references
T4.6!C77:I77, T4.3!C80:I80, T4.7!C88:I88, T4.9!C100:I100, T4.1!C87:I87, T4.4!C67:I67What it means
- Wholesale and retail (S$7,262) and finance and insurance (S$7,019) pay about the same as tech.
Part 3 · Over time
Pay over time and 2026 outlook
Data scientist pay rose from S$8,167 in 2020 to S$10,111 in 2025. No title here is steady enough to project.
Official medians for the last six years, then a projection for June 2026.
| Occupation | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | Trend |
|---|---|---|---|---|---|---|---|
| Statistical officer/Data analyst | – | 5,446 | 5,335 | 6,235 | 8,356 | 5,869 | |
| Data scientist | 8,167 | 8,110 | 10,350 | 9,590 | 9,047 | 10,111 | |
| Data engineer | – | – | – | – | – | 8,721 | |
| Data/Database administrator | – | 6,559 | 5,585 | 4,867 | 6,717 | 8,471 | |
| Statistician | – | – | – | 4,382 | 4,720 | 7,723 |
Median gross monthly wage, June of each year, S$. "–" = not published, or the job code changed in a way that cannot be linked one-to-one. Earlier years use SSOC 2020 codes, linked to SSOC 2024 with SingStat's official correspondence table. MOM advises that single-year changes are noisy because the survey is a sample; look at the direction over several years. Source: MOM Occupational Wages 2020 to 2025, Table 4.
June 2026 projection Estimate
| Occupation | June 2025 (MOM) | June 2026 projection | 80% range | Range |
|---|---|---|---|---|
| Statistical officer/Data analyst | 5,869 | Not projected: too volatile | ||
| Data scientist | 10,111 | Not projected: too volatile | ||
| Data engineer | 8,721 | Not projected: not enough history | ||
| Data/Database administrator | 8,471 | Not projected: too volatile | ||
| Statistician | 7,723 | Not projected: too volatile | ||
Foundific projection v1, not official data. Central estimate = average of the last two MOM medians + economy-wide wage growth (3.73% a year, from MOM median income and the MAS inflation forecast). Tested on 2025: typical error 8.1%; 78.7% of actual values fell inside the 80% range. How the projection works.
What it means
- Data analyst pay swung: S$8,356 in 2024, then S$5,869 in 2025. MOM warns that single-year changes are noisy because the survey is a sample.
- No projections: every title moved too much between years, or has too little history.
- Estimate: projections are ours, not MOM data. MOM's June 2026 figures are due around mid-2027 and will replace them.
Part 4 · AI impact
Is data work affected by AI?
The ILO rates data analysts, data scientists and data engineers High.
Based on the International Labour Organization's 2025 index, which scores every core task of a job from 0 (AI cannot help) to 1 (AI could do nearly all of it).
Statistical officer/Data analyst
HighAI exposure
Not exposedVery high
AI can do a large part of many tasks, so the job is likely to change noticeably.
- Most exposed taskPlanning and organizing surveys and other statistical…
- Least exposed taskSupervising the work of mathematical, actuarial
- In numbersAI could do a large part of 9 of its 10 main tasks.
Data engineer
HighAI exposure
Not exposedVery high
AI can do a large part of many tasks, so the job is likely to change noticeably.
- Most exposed taskDesigning, constructing, modifying, integrating
- Least exposed taskPerforming the operational establishment and preventive…
- In numbersAI could do a large part of 5 of its 6 main tasks.
Statistical officer/Data analystSSOC 21231
Highexposure to generative AI
- Not exposed
- Minimal
- Some
- Moderate
- High
- Very high
Scored as ILO group 2120 Mathematicians, actuaries and statisticians. Average task score 0.56, higher than 94% of the 427 jobs the ILO scored.
Data engineerSSOC 25213
Highexposure to generative AI
- Not exposed
- Minimal
- Some
- Moderate
- High
- Very high
Scored as ILO group 2521 Database designers and administrators. Average task score 0.57, higher than 95% of the 427 jobs the ILO scored.
Eight factors, role by role
| Factor | Statistical officer/Data analyst | Data engineer |
|---|---|---|
| 1Exposure levelThe ILO's rating for the whole job, from not exposed up to very high. | High | High |
| 2Average task scoreHow much of each core task generative AI could do, averaged. 0 means none, 1 means nearly all. | 0.56 higher than 94% of jobs | 0.57 higher than 95% of jobs |
| 3Tasks AI could do much ofTasks scoring 0.5 or more. These are the parts of the job most likely to change. | 9 of 10 | 5 of 6 |
| 4Hands-on or people tasksTasks scoring under 0.25: physical, in-person or judgement work that AI barely touches. | 0 of 10 | 0 of 6 |
| 5How even the exposure isEven means AI touches most tasks a little. Uneven means a few tasks are exposed and the rest are not. | Even (0.08) | Even (0.08) |
| 6Most exposed taskWhere AI tools are likely to show up first. | Planning and organizing surveys and other statistical… 0.67 | Designing, constructing, modifying, integrating… 0.67 |
| 7Least exposed taskThe task AI can help with least. | Supervising the work of mathematical, actuarial and… 0.35 | Performing the operational establishment and preventive… 0.43 |
| 8Pay trend so farChange in the MOM median since the first year on record. Any AI effect would show here in later years. | +8% S$5,446 (2021) to S$5,869 (2025) | Not enough years |
Most and least exposed tasks
Statistical officer/Data analyst
Most exposed tasks
- 0.67Planning and organizing surveys and other statistical collections, and…
- 0.63Designing and putting into operation pension schemes and life, health, social…
- 0.63Evaluating, processing, analysing, and interpreting statistical data and…
Least exposed tasks
- 0.35Supervising the work of mathematical, actuarial and statistical assistants…
- 0.53Preparing scientific papers and reports
- 0.54Studying, improving and developing mathematical, actuarial and statistical…
Data engineer
Most exposed tasks
- 0.67Designing, constructing, modifying, integrating, implementing and testing…
- 0.62Designing and developing database architecture, data structures, tables…
- 0.61Developing policies and procedures for database access and usage and for the…
Least exposed tasks
- 0.43Performing the operational establishment and preventive maintenance of…
- 0.53Developing and implementing data administration policy, documentation…
- 0.54Conducting research and providing advice on the selection, application and…
Compared with our other guides
Source: ILO Working Paper 140, Generative AI and Jobs: A Refined Global Index of Occupational Exposure (Gmyrek et al., 2025), CC BY 4.0. Singapore jobs matched to ILO groups with the SingStat SSOC 2024 to ISCO-08 correspondence table. Pay: MOM Occupational Wages. The ILO scores international job groups, not Singapore titles. How we read the AI scores.
Cell references
SSOC 21231 to ISCO 2120 (SSOC2024-ISCO08!B105); SSOC 25213 to ISCO 2521 (SSOC2024-ISCO08!B343)What it means for data work
- Average task score: 0.56 for analysts, scientists and statisticians, higher than 94% of the 427 jobs the ILO scored. 0.57 for data engineers.
- Most exposed tasks: planning surveys and statistical work, and writing up results.
- Least exposed task: supervising other analysts.
- What exposure measures: how much of the work AI could do or speed up. It does not measure job cuts. Employers decide how to use AI.
Part 5 · Using the figures
Which figure should you compare with?
Titles vary between employers, so compare what you do, not only what you are called.
| You are | Compare with | Figure |
|---|---|---|
| Choosing a data course | Data and analytics courses, six months after graduating | S$4,550 to S$6,000 |
| Data analyst, early career | Data analyst, age 25 to 29 | S$5,833 |
| Data analyst at a tech firm | Information and communications figure | S$7,263 |
| Data scientist, early career | Data scientist, age 25 to 29 | S$7,000 |
| Data scientist in your thirties | Data scientist, age 30 to 39 | S$9,693 |
| Data engineer | Data engineer row | S$8,721 |
About these figures
What the pay figures includeMonthly gross pay with allowances and overtime, without bonuses or employer CPF
Every figure is monthly, includes allowances and overtime, and excludes bonuses and employer CPF.
| Measure | Includes | Excludes |
|---|---|---|
| Basic wage | Basic pay | Allowances, overtime, bonus, employer CPF |
| Gross wage | Basic + allowances + overtime + commissions | Bonus, employer CPF, lump sums |
| Graduate salary | Same as gross, full-time permanent jobs only | Bonus, employer CPF |
- S$5,869 × 12 = S$70,428 a year before bonus. It is not a total package.
What this data does not coverBonuses are excluded, and one employer's data analyst can be another's data scientist.
Bonuses are excluded, and one employer's data analyst can be another's data scientist.
- Titles vary: MOM records the title the employer reports.
- Bonuses: excluded from every figure.
- Residents only: figures cover full-time Singapore citizens and permanent residents. Staff on work passes are not included.
- Small firms with fewer than 25 staff are outside the survey.
Related guides
Sources
MOM Occupational Wages 2025 and MOE Graduate Employment Survey 2025
- MOM, Occupational Wages 2025, Tables 1 to 4. June 2025, released 30 June 2026. SSOC 21231, 21222, 25213, 25211, 21221. Exact cells are listed under each table.
- MOE, NUS GES 2025. Bachelor of Science (Data Science and Analytics); Bachelor of Science (Business Analytics); Bachelor of Computing (Information Systems).
- MOE, SIT GES 2025. Bachelor of Science with Honours in Applied Artificial Intelligence.
- MOE, SMU GES 2025. Information Systems.
- MOE, SUSS GES 2025. Bachelor of Science in Business Analytics.
- MOM, Coverage and Methodology 2025.
- ILO generative AI exposure index 2025, matched to SSOC through the SingStat correspondence table.