Science Applications International (SAIC) EBITDA (2012 - 2026)
Science Applications International (SAIC) recorded EBITDA of $191 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 9.8% from $174 million a year earlier but down 12.8% from the prior quarter.
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Analysis
Science Applications International (SAIC) EBITDA (2012 - 2026) Analysis & Trends
On a TTM basis, Science Applications International's EBITDA came in at $749 million as of Jul 31, 2026, up 7.0% year-over-year; for FY2026 (ended Jan 30, 2026), it was $670 million, down 4.7% from FY2025.
- Annual EBITDA has a five-year compound annual growth rate of 3.3% (FY2021 to FY2026).
- Across earlier fiscal years, EBITDA came in at $703 million in FY2025 (-20.4%), $883 million in FY2024 (+34.2%), $658 million in FY2023 (+4.9%) and $627 million in FY2022 (+10.2%).
- Quarterly EBITDA has ranged from $115 million in fiscal Q4 2024 to $398 million in fiscal Q2 2024 over the past five years.
- On a year-over-year basis, EBITDA rose in five of the last eight quarters, with growth averaging 11.7%.
- Peak year-over-year performance for EBITDA in the last five years was growth of 141.2% in fiscal Q2 2024, against a decline of 57.8% in fiscal Q2 2025 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $219 million (Q1 2027), $173 million (Q4 2026) and $166 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 1.21 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 1.02 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 624.64 Mn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 503.70 Mn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 591.24 Mn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 412.93 Mn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 253.61 Mn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 285.25 Mn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 184.32 Mn |
| 10 | Science Applications International | 5.50 Bn | 5.04 Bn | 239.00 Mn | 191.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 191.00 Mn |
| May 1, 2026 | 219.00 Mn |
| Jan 30, 2026 | 173.00 Mn |
| Oct 31, 2025 | 166.00 Mn |
| Aug 1, 2025 | 174.00 Mn |
| May 2, 2025 | 157.00 Mn |
| Jan 31, 2025 | 174.00 Mn |
| Nov 1, 2024 | 195.00 Mn |
| Aug 2, 2024 | 168.00 Mn |
| May 3, 2024 | 166.00 Mn |
| Feb 2, 2024 | 115.00 Mn |
| Nov 3, 2023 | 177.00 Mn |
| Aug 4, 2023 | 398.00 Mn |
| May 5, 2023 | 193.00 Mn |
| Feb 3, 2023 | 157.00 Mn |
| Oct 28, 2022 | 170.00 Mn |
| Jul 29, 2022 | 165.00 Mn |
| Apr 29, 2022 | 166.00 Mn |
| Jan 28, 2022 | 127.00 Mn |
| Oct 29, 2021 | 158.00 Mn |
API Access
Science Applications International EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=SAIC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "SAIC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=SAIC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();