# Jobstreet Malaysia & Singapore Job Scraper (`crawlify/jobstreet-my-sg-scraper`) Actor Extract enriched job listings from Jobstreet Malaysia & Singapore. Get structured salary ranges, auto-detected skills, experience levels, work arrangements, and a quality score — all in one clean dataset. - **URL**: https://apify.com/crawlify/jobstreet-my-sg-scraper.md - **Developed by:** [Crawlify](https://apify.com/crawlify) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Jobstreet Malaysia & Singapore Job Scraper Extract structured, enriched job listings from **[Jobstreet Malaysia](https://my.jobstreet.com)** and **[Jobstreet Singapore](https://sg.jobstreet.com)** — ready for analysis, reporting, or automation. ### What does Jobstreet Scraper do? Enter any job keywords, pick a country (or both), and get a clean dataset back in seconds. Unlike other Jobstreet scrapers that return raw, unprocessed text, this actor enriches every listing with: - **Structured salary data** — parsed `min`, `max`, `currency`, `period`, and annualised figures instead of a raw string like "RM 5,000 – RM 6,999 per month" - **Auto-detected skills** — 80+ tech and process skills (Python, AWS, Docker, Agile…) identified from title, teaser, and bullet points - **Experience level** — Junior / Mid / Senior / Management auto-inferred from the job title - **Work arrangement** — On-site / Hybrid / Remote pulled directly from the listing - **Completeness score** — 0–100 quality rating so you can instantly filter out low-signal listings ### Why use this scraper? | Use case | How this actor helps | |---|---| | **Salary benchmarking** | Structured `salary.min/max/annualMin/annualMax` fields — paste straight into Excel or Power BI | | **Talent market research** | See which skills dominate listings for any role across MY and SG | | **Competitor hiring analysis** | Filter by company, classification, or location | | **Job alert automation** | Schedule daily runs and pipe results to Slack or Google Sheets via Apify integrations | | **Academic / HR research** | Clean, structured dataset covering two major ASEAN job markets | ### How to use Jobstreet Scraper 1. Open the **Input** tab 2. Enter your **keywords** — e.g. `"software engineer"`, `"data analyst"`, `"product manager"` 3. Select **countries** — Malaysia (`MY`), Singapore (`SG`), or both 4. Optionally filter by **location**, **date posted**, or **work type** 5. Click **Start** — your dataset is ready in the **Output** tab within seconds No account or login required. ### Input | Field | Type | Default | Description | |---|---|---|---| | `keywords` | string | — | Job search keywords (**required**), e.g. `"devops engineer"` | | `countries` | array | `["MY"]` | One or both of `"MY"` (Malaysia) and `"SG"` (Singapore) | | `location` | string | all | English city name, e.g. `"Kuala Lumpur"`, `"Penang"`, `"Singapore"` | | `maxResults` | integer | unlimited | Cap total results (useful for exploratory or budgeted runs) | | `dateRange` | select | last 7 days | Any time / 1 / 3 / 7 / 14 / 30 days | | `workType` | select | all | Full time / Part time / Contract / Casual | | `sortMode` | select | most recent | Most recent or most relevant | > **Location tip:** Use English city names. `"Penang"` works; `"Pulau Pinang"` returns zero results. ### Output Each job is a structured JSON object. Example: ```json { "jobId": "92506170", "title": "Senior Software Developer", "company": "Vmall Enterprise Sdn Bhd", "companyUrl": "https://my.jobstreet.com/companies/vmall-enterprise-168559357935778", "companyLogoUrl": "https://bx-branding-gateway.cloud.seek.com.au/logo.png", "location": "Subang Jaya, Selangor", "country": "MY", "salary": { "raw": "RM 5,000 – RM 6,999 per month", "currency": "MYR", "min": 5000, "max": 6999, "period": "month", "annualMin": 60000, "annualMax": 83988 }, "workType": "Full time", "workArrangement": "Hybrid", "classification": "Information & Communication Technology", "subClassification": "Developers/Programmers", "teaser": "Lead a team of developers responsible for building new and supporting existing systems.", "bulletPoints": ["5+ years of experience", "Team leadership", "Agile environment"], "skills": ["Python", "Docker", "REST API", "Git", "Linux", "Agile"], "experienceLevel": { "level": "Senior", "yearsRequired": "5+" }, "isFeatured": false, "listingDate": "2026-06-04T00:35:52Z", "listingDateDisplay": "1h ago", "jobUrl": "https://my.jobstreet.com/job/92506170", "completenessScore": 85, "scrapedAt": "2026-06-04T02:30:00.000000+00:00" } ```` Download the dataset as **JSON, CSV, Excel, XML, or RSS** from the Output tab or via the Apify API. ### Data fields | Field | Format | Description | |---|---|---| | `jobId` | string | Jobstreet unique job ID | | `title` | string | Job title | | `company` | string | Employer name | | `companyUrl` | link | Company profile on Jobstreet | | `companyLogoUrl` | link | Company logo image URL | | `location` | string | City and state/region | | `country` | string | `MY` or `SG` | | `salary.currency` | string | `MYR` or `SGD` | | `salary.min` / `salary.max` | number | Salary range in local currency | | `salary.annualMin` / `salary.annualMax` | number | Annualised figure (e.g. monthly × 12) | | `workType` | string | Full time / Part time / Contract / Casual | | `workArrangement` | string | On-site / Hybrid / Remote | | `classification` | string | Jobstreet job category | | `subClassification` | string | Jobstreet sub-category | | `teaser` | string | Short job summary shown in search results | | `bulletPoints` | array | Key selling points listed by the employer | | `skills` | array | Auto-extracted tech/process skills (80+ recognised) | | `experienceLevel.level` | string | Junior / Mid / Senior / Management / Not specified | | `experienceLevel.yearsRequired` | string | e.g. `"3-5"` or `"5+"` | | `isFeatured` | boolean | Whether the listing is a sponsored/promoted ad | | `listingDate` | ISO datetime | When the job was posted | | `listingDateDisplay` | string | Human-readable age, e.g. `"2d ago"` | | `completenessScore` | integer | 0–100 data quality rating | | `jobUrl` | link | Direct link to the full listing on Jobstreet | | `scrapedAt` | ISO datetime | Timestamp of when this record was collected | ### Pricing & cost estimation This actor uses **pay-per-result** billing — you only pay for jobs actually returned. | Scenario | Jobs | Estimated cost | |---|---|---| | Quick test run, last 24h | 30–50 | < $0.10 | | 500 SG tech jobs, last 7 days | 500 | ~$1.00 | | Full MY software listings, any time | ~3 000 | ~$6.00 | Use `maxResults` to cap spend on exploratory runs — start small to validate the data shape before going full scale. ### Tips for best results - **Benchmark across markets** — include both `MY` and `SG` in `countries`, then group by the `country` field in Excel or any BI tool - **Daily job alerts** — set `dateRange: "1"` and schedule the actor to run every morning; connect to Slack or Google Sheets via Apify integrations - **Cap spend on large queries** — set `maxResults: 100` for a quick sample before running the full query - **Filter by quality** — post-process with `completenessScore >= 50` to focus on listings that include salary and work arrangement - **Salary-only analysis** — filter where `salary.min` is not null to isolate the ~30–40% of listings that disclose pay ### FAQ **Is scraping Jobstreet legal?** This actor collects publicly visible job listings — the same data any visitor sees in their browser. Always comply with Jobstreet's Terms of Service and applicable data protection laws in your jurisdiction. Do not collect or store personal candidate data. **Does this include the full job description?** The full description is not included in the dataset — skills and experience level are extracted from the title, teaser, and employer bullet points. To read the full listing, follow the `jobUrl` field. **Can I scrape Indonesia or Philippines too?** Currently only Malaysia and Singapore are supported. Open a request in the Issues tab if you need additional countries. **Something broken or missing?** Open an issue in the Issues tab. Include the keywords and input you used, plus any error from the run log. Custom scraping solutions are also available. # Actor input Schema ## `keywords` (type: `string`): Job search keywords (e.g. 'software engineer', 'data analyst', 'product manager'). ## `countries` (type: `array`): Which Jobstreet sites to scrape. Enter MY (Malaysia) and/or SG (Singapore). ## `location` (type: `string`): Filter by English city or region name (e.g. 'Kuala Lumpur', 'Penang', 'Singapore'). Leave empty for all locations. ## `maxResults` (type: `integer`): Maximum total jobs to return. Leave empty to fetch all available results (up to 3 000 per query). ## `dateRange` (type: `string`): Only include jobs posted within this period. ## `workType` (type: `string`): Filter by employment type. ## `sortMode` (type: `string`): How to order results. ## Actor input object example ```json { "keywords": "software engineer", "countries": [ "MY" ], "dateRange": "7", "workType": "", "sortMode": "ListedDate" } ``` # Actor output Schema ## `dataset` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": "software engineer", "countries": [ "MY" ] }; // Run the Actor and wait for it to finish const run = await client.actor("crawlify/jobstreet-my-sg-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": "software engineer", "countries": ["MY"], } # Run the Actor and wait for it to finish run = client.actor("crawlify/jobstreet-my-sg-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": "software engineer", "countries": [ "MY" ] }' | apify call crawlify/jobstreet-my-sg-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlify/jobstreet-my-sg-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Jobstreet Malaysia & Singapore Job Scraper", "description": "Extract enriched job listings from Jobstreet Malaysia & Singapore. Get structured salary ranges, auto-detected skills, experience levels, work arrangements, and a quality score — all in one clean dataset.", "version": "1.0", "x-build-id": "GkTt2gDweV3qPeOaE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlify~jobstreet-my-sg-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlify-jobstreet-my-sg-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlify~jobstreet-my-sg-scraper/runs": { "post": { "operationId": "runs-sync-crawlify-jobstreet-my-sg-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlify~jobstreet-my-sg-scraper/run-sync": { "post": { "operationId": "run-sync-crawlify-jobstreet-my-sg-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "keywords" ], "properties": { "keywords": { "title": "Search Keywords", "type": "string", "description": "Job search keywords (e.g. 'software engineer', 'data analyst', 'product manager').", "default": "software engineer" }, "countries": { "title": "Countries", "type": "array", "description": "Which Jobstreet sites to scrape. Enter MY (Malaysia) and/or SG (Singapore).", "items": { "type": "string" }, "default": [ "MY" ] }, "location": { "title": "Location Filter", "type": "string", "description": "Filter by English city or region name (e.g. 'Kuala Lumpur', 'Penang', 'Singapore'). Leave empty for all locations." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum total jobs to return. Leave empty to fetch all available results (up to 3 000 per query)." }, "dateRange": { "title": "Date Posted", "enum": [ "", "1", "3", "7", "14", "30" ], "type": "string", "description": "Only include jobs posted within this period.", "default": "7" }, "workType": { "title": "Work Type", "enum": [ "", "fullTime", "partTime", "contract", "casual" ], "type": "string", "description": "Filter by employment type.", "default": "" }, "sortMode": { "title": "Sort Order", "enum": [ "", "ListedDate", "KeywordRelevance" ], "type": "string", "description": "How to order results.", "default": "ListedDate" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```