Science Applications International (SAIC) Operating Expenses (2012 - 2026)
Science Applications International's Operating Expenses came in at $87 million for fiscal Q2 2027 (quarter ended Jul 31, 2026), up 16.0% from $75 million a year earlier and up 4.8% from the prior quarter.
Science Applications International (SAIC) Operating Expenses (2012 - 2026) Analysis & Trends
Over the trailing twelve months to Jul 31, 2026, Science Applications International reported Operating Expenses of $356 million, up 4.4% year-over-year; for FY2026 (ended Jan 30, 2026), it came in at $350 million, up 3.2% from FY2025.
- Operating Expenses carries a five-year compound annual growth rate of -2.9% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $339 million in FY2025 (-9.4%), $374 million in FY2024 (-3.4%), $387 million in FY2023 (-3.3%) and $400 million in FY2022 (-1.5%).
- The five-year range for quarterly Operating Expenses is $75 million (fiscal Q2 2026) to $114 million (fiscal Q4 2024).
- Year-over-year, Operating Expenses increased in three of the last eight quarters, with growth averaging 0.2%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q3 2026 (growth of 21.7%), and the weakest in fiscal Q4 2025 (a decline of 17.5%).
- Business Quant data shows SAIC's Operating Expenses at $83 million (Q1 2027), $85 million (Q4 2026) and $101 million (Q3 2026) in the three fiscal quarters before Q2 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 822.22 Mn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 12.44 Mn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 747.88 Mn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 634.01 Mn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 722.71 Mn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Science Applications International | 5.50 Bn | 5.04 Bn | 239.00 Mn | 87.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 87.00 Mn |
| May 1, 2026 | 83.00 Mn |
| Jan 30, 2026 | 85.00 Mn |
| Oct 31, 2025 | 101.00 Mn |
| Aug 1, 2025 | 75.00 Mn |
| May 2, 2025 | 89.00 Mn |
| Jan 31, 2025 | 94.00 Mn |
| Nov 1, 2024 | 83.00 Mn |
| Aug 2, 2024 | 77.00 Mn |
| May 3, 2024 | 85.00 Mn |
| Feb 2, 2024 | 114.00 Mn |
| Nov 3, 2023 | 87.00 Mn |
| Aug 4, 2023 | 89.00 Mn |
| May 5, 2023 | 84.00 Mn |
| Feb 3, 2023 | 104.00 Mn |
| Oct 28, 2022 | 88.00 Mn |
| Jul 29, 2022 | 94.00 Mn |
| Apr 29, 2022 | 101.00 Mn |
| Jan 28, 2022 | 112.00 Mn |
| Oct 29, 2021 | 99.00 Mn |
Science Applications International Operating Expenses 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=operating-expenses&ticker=SAIC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=SAIC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();