# LinkedIn Job Search with German-Language Filtering (`sizable_dizi/linkedin-scrapper`) Actor

Scrape LinkedIn jobs by title and skip roles that require fluent German. De-duplicated results you can export to Google Sheets on a schedule.

- **URL**: https://apify.com/sizable\_dizi/linkedin-scrapper.md
- **Developed by:** [Simran](https://apify.com/sizable_dizi) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## LinkedIn Jobs Scraper — with German-language filtering

Search LinkedIn jobs across several job titles at once and automatically filter out roles that **require fluent German** — a filter LinkedIn's own search doesn't offer. Built for people job-hunting in German-speaking markets who don't (yet) speak fluent German.

Results come back as a clean, de-duplicated dataset you can export to CSV/Excel or send to Google Sheets on a schedule.

### What it does

- Runs one search per job title you enter (e.g. *BI Analyst*, *Data Analyst*, *Datenanalyst*) and merges the results.
- Reads each job description and detects the **German** and **English** language requirements separately, quoting the exact wording found.
- Optionally drops roles that require German, and postings written entirely in German.
- Remembers jobs between runs, so scheduled runs only return **new** postings (no duplicates).
- Uses LinkedIn's **public, logged-out** pages — no account or login needed.

### Main input options

- **Search terms** — one search per job title.
- **Location** — city, region, or country (e.g. *Germany*).
- **Date posted** — any time / past 24 hours / week / month.
- **Experience levels** — pick any (defaults skip Director/Executive).
- **Job type, Workplace type, Sort by** — standard LinkedIn filters.
- **Max jobs per term** — cap per title.
- **Exclude jobs requiring fluent German** — on by default.
- **Exclude job posts written in German** — on by default.
- **Keep jobs with unclear German requirement** — on by default (kept for manual review).
- **Only new jobs** — skip jobs seen in previous runs (recommended for schedules).
- **Proxy** — Datacenter works on the free plan.

### How the language filter works

For each job, the Actor looks at the words next to each mention of *German/Deutsch* and *English/Englisch* and labels the required level:

`Native` · `Fluent` · `Very good` · `Good` · `Intermediate` · `Basic` · `Nice to have` · `Required` · `Not required` · `Mentioned (unspecified)` · `No requirement`

Each label comes with the exact matched phrase (`germanEvidence` / `englishEvidence`) so you can see why it was labelled that way. By default, jobs where German is required (Good level or above) or where the whole post is in German are removed; ambiguous ones are kept and flagged.

### Output fields

Each job includes:

- **Core:** `title`, `company`, `companyUrl`, `location`, `url`, `postedDate`, `matchedTerm`
- **Language:** `germanRequirement`, `germanEvidence`, `germanLevel`, `englishRequirement`, `englishEvidence`, `englishLevel`, `descriptionLanguage`
- **Signals:** `applicants`, `daysOld`, `postedText`, `reposted`, `hiringManager`, `hiringManagerProfile`, `salary`
- **Details:** `seniorityLevel`, `employmentType`, `jobFunction`, `industries`, `description`
- **Housekeeping:** `firstSeen`, `scrapedAt`, `jobId`

> `applicants`, `hiringManager`, and `salary` are best-effort — they appear when LinkedIn shows them on the public page, and are empty otherwise.

### Exporting the results

- **Manual:** open the run's dataset and click **Export** (CSV, Excel, JSON).
- **Automatic (schedule):** connect a **Google Sheets** integration from the **Integrations** tab, using **append** mode into one sheet. Combined with *Only new jobs*, your sheet becomes a clean, growing list with no duplicates.

### Notes & limits

- Uses LinkedIn's public guest pages; please use the results responsibly and in line with LinkedIn's terms.
- The language filter is a text heuristic, not perfect — the `Evidence` fields let you double-check.
- LinkedIn's guest search returns a limited pool per query, so narrow by title, location, or date for the best coverage.

# Actor input Schema

## `searchTerms` (type: `array`):

One LinkedIn search per term. For your first test, trim this to a single term.

## `location` (type: `string`):

City, region, or country to search in (e.g. Germany, Berlin).

## `datePosted` (type: `string`):

How recently the job was posted.

## `jobType` (type: `string`):

Employment type filter.

## `experienceLevels` (type: `array`):

Select one or more. Leave Director/Executive unchecked to skip senior roles.

## `workplaceType` (type: `string`):

On-site, remote, or hybrid.

## `sortBy` (type: `string`):

Order of results returned by LinkedIn.

## `maxJobsPerTerm` (type: `integer`):

Keep this low (e.g. 5) for your first test run.

## `excludeGermanRequired` (type: `boolean`):

Drop jobs whose description requires fluent/native German (e.g. 'gute Deutschkenntnisse', 'verhandlungssicher', C1/C2).

## `excludeGermanLanguagePosts` (type: `boolean`):

Drop jobs whose description is written entirely in German. Turn OFF to keep them (still tagged descriptionLanguage='de').

## `keepUnclearGerman` (type: `boolean`):

German mentioned but level ambiguous — keep and flag for manual review.

## `onlyNewJobs` (type: `boolean`):

Skip jobs already seen in previous runs (recommended for scheduled runs and for appending to a Google Sheet without duplicates).

## `datasetName` (type: `string`):

Named dataset that accumulates all jobs across runs.

## `seenStoreName` (type: `string`):

Named key-value store that remembers which job IDs were already scraped.

## `seenRetentionDays` (type: `integer`):

After this many days a job can resurface as 'new' again.

## `proxyConfiguration` (type: `object`):

Datacenter (default) works on the free plan. Switch to Residential later for reliability.

## Actor input object example

```json
{
  "searchTerms": [
    "BI Analyst",
    "Business Intelligence Analyst",
    "Data Analyst",
    "Business Analyst",
    "Datenanalyst"
  ],
  "location": "Germany",
  "datePosted": "r86400",
  "jobType": "",
  "experienceLevels": [
    "1",
    "2",
    "3",
    "4"
  ],
  "workplaceType": "",
  "sortBy": "DD",
  "maxJobsPerTerm": 50,
  "excludeGermanRequired": true,
  "excludeGermanLanguagePosts": true,
  "keepUnclearGerman": true,
  "onlyNewJobs": true,
  "datasetName": "linkedin-jobs",
  "seenStoreName": "linkedin-seen",
  "seenRetentionDays": 45,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `jobs` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("sizable_dizi/linkedin-scrapper").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("sizable_dizi/linkedin-scrapper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call sizable_dizi/linkedin-scrapper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,sizable_dizi/linkedin-scrapper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/4fFUScQMvvytIaVd2/builds/hwScGxpndmkSdcSu6/openapi.json