{
    "url": "https://www.spotsalary.com/salary/data-scientists/jakarta-id-1360771077",
    "canonical": "https://www.spotsalary.com/salary/data-scientists/jakarta-id-1360771077",
    "headline": "Data scientists Salary in Jakarta, Indonesia",
    "description": "Median Data scientists salary in Jakarta, Indonesia is Rp175.9M per year. Compare P10–P90 salary bands by experience, take-home pay and a five-year outlook.",
    "occupation": {
        "name": "Data scientists",
        "slug": "data-scientists",
        "family": null,
        "soc_code": null,
        "aliases": [],
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    },
    "location": {
        "name": "Jakarta, Indonesia",
        "slug": "jakarta-id-1360771077",
        "type": "city",
        "iso2": "ID",
        "currency": "IDR"
    },
    "period": 2026,
    "confidence": 68,
    "status": "published",
    "method": "nearest_neighbor",
    "updated_at": "2026-11-01T03:01:01+00:00",
    "salary_bands": [
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            "level": "entry",
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                2
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            "p10": 73510996.17,
            "p25": 91480344.4,
            "p50": 114350447.32,
            "p75": 132646500.59,
            "p90": 158783739.63,
            "base_share": 95,
            "bonus_share": 5,
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        {
            "level": "mid",
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            "p10": 113093834.52,
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            "p75": 204071542.38,
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        {
            "level": "senior",
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                9
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            "p10": 186604839.16,
            "p25": 232219338.79,
            "p50": 290274200.88,
            "p75": 336718050.56,
            "p90": 403066436.35,
            "base_share": 80,
            "bonus_share": 10,
            "equity_share": 10
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        {
            "level": "executive",
            "years_experience": [
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                15
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            "p10": 316662750.93,
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            "p90": 683991537.49,
            "base_share": 65,
            "bonus_share": 15,
            "equity_share": 20
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    "take_home": {
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        "tax_rate": 11.589431569879698,
        "top_rate": null,
        "method": "progressive",
        "label": "progressive brackets",
        "standard_deduction": 0,
        "rebate": 0,
        "source": "PwC Worldwide Tax Summaries",
        "source_url": "https://taxsummaries.pwc.com/indonesia/individual/taxes-on-personal-income",
        "retrieved_at": "2026-10-23T00:00:00.000000Z",
        "verified": true,
        "notes": "2026 PPh 21 resident employment; excludes deductions",
        "bands": [
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                "source": "PwC Worldwide Tax Summaries",
                "source_url": "https://taxsummaries.pwc.com/indonesia/individual/taxes-on-personal-income",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
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                "notes": "2026 PPh 21 resident employment; excludes deductions"
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                "taxable": 175923753.56,
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                "net_monthly": 12961265.877166666,
                "method": "progressive",
                "top_rate": null,
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                "rebate": 0,
                "source": "PwC Worldwide Tax Summaries",
                "source_url": "https://taxsummaries.pwc.com/indonesia/individual/taxes-on-personal-income",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
                "verified": true,
                "notes": "2026 PPh 21 resident employment; excludes deductions"
            },
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                "source": "PwC Worldwide Tax Summaries",
                "source_url": "https://taxsummaries.pwc.com/indonesia/individual/taxes-on-personal-income",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
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                "notes": "2026 PPh 21 resident employment; excludes deductions"
            },
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                "net_monthly": 33369989.14770833,
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                "source": "PwC Worldwide Tax Summaries",
                "source_url": "https://taxsummaries.pwc.com/indonesia/individual/taxes-on-personal-income",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
                "verified": true,
                "notes": "2026 PPh 21 resident employment; excludes deductions"
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    "outlook": {
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                        "name": "Hiring demand",
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                    {
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                    {
                        "name": "Real wage growth",
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                        "weight": "high",
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                    {
                        "name": "Scenario growth",
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                "year": 2027,
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                    {
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                    {
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                        "name": "Automation exposure",
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                    {
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                        "name": "Real wage growth",
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            {
                "year": 2031,
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                        "name": "Inflation (CPI)",
                        "note": "3.5% annual price growth",
                        "weight": "high",
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                    },
                    {
                        "name": "Wage growth",
                        "note": "5.5% nominal wage trend",
                        "weight": "high",
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                    {
                        "name": "Role demand trend",
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                    {
                        "name": "Hiring demand",
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                        "weight": "medium",
                        "direction": "up"
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                    {
                        "name": "Automation exposure",
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                    {
                        "name": "Real wage growth",
                        "note": "3.5% after 3.5% inflation",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Scenario growth",
                        "note": "7.0% modelled nominal growth",
                        "weight": "high",
                        "direction": "up"
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                ]
            }
        ]
    },
    "skills": [],
    "sources": [
        {
            "name": "Indonesia",
            "url": null,
            "type": "nearest_donor",
            "tier": "derived"
        },
        {
            "name": "Malaysia",
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            "type": "nearest_donor",
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        },
        {
            "name": "Bangladesh",
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            "type": "nearest_donor",
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        {
            "name": "India",
            "url": null,
            "type": "nearest_donor",
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    ],
    "faqs": [
        {
            "question": "What is the average salary of a Data scientists in Jakarta, Indonesia?",
            "answer": "SpotSalary models a median annual salary of Rp175.9M for a Data scientists in Jakarta, Indonesia, or about Rp14,660,313 per month before tax. The middle 50% of the estimate ranges from Rp140.7M to Rp204.1M, with a full P10–P90 range of Rp113.1M to Rp244.3M. This is a modelled estimate, not a job offer."
        },
        {
            "question": "How much does an entry-level Data scientists earn in Jakarta, Indonesia?",
            "answer": "The entry-level band for a Data scientists in Jakarta, Indonesia centres on Rp114.4M per year (P25–P75: Rp91.5M–Rp132.6M). Entry-level pay typically covers the first 2 years of experience and depends on company size, skills and responsibilities."
        },
        {
            "question": "How much does a senior or executive Data scientists earn in Jakarta, Indonesia?",
            "answer": "The executive band for a Data scientists in Jakarta, Indonesia has a median of Rp492.6M per year and a P75 of Rp571.4M. Senior and executive packages often include a larger bonus and equity component; this benchmark shows the total-compensation split for each level."
        },
        {
            "question": "What is the salary outlook for a Data scientists in Jakarta, Indonesia?",
            "answer": "The outlook is growing. In the base scenario, median pay reaches Rp246.7M by 2031, about 40.3% above today before inflation and 3.5% per year in real terms after 3.5% inflation. Scenario bands widen over time and are not guarantees."
        },
        {
            "question": "What is the take-home pay for a Data scientists in Jakarta, Indonesia?",
            "answer": "After an effective income tax rate of 11.6%, the mid-level Data scientists in Jakarta, Indonesia takes home about Rp155,535,191 per year, or Rp12,961,266 per month. The estimate uses imported national tax brackets and does not include social contributions or local levies."
        },
        {
            "question": "How does SpotSalary calculate these salary estimates?",
            "answer": "Estimates are anchored to external market signals — GDP per capita PPP, inflation, wage growth, cost of living, demand and automation exposure — and synthesised with AI. Deterministic validation rejects implausible outputs. This report carries 68% confidence."
        }
    ],
    "related": {
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        ],
        "occupation_hub": "https://www.spotsalary.com/occupations/data-scientists",
        "location_hub": "https://www.spotsalary.com/locations/jakarta-id-1360771077",
        "all_salaries": "https://www.spotsalary.com/salaries"
    },
    "citation": {
        "plain": "Data scientists Salary in Jakarta, Indonesia. SpotSalary. https://www.spotsalary.com/salary/data-scientists/jakarta-id-1360771077",
        "updated_at": "2026-11-01T03:01:01+00:00"
    }
}