The race condition in the original code occurs because multiple threads can simultaneously check if a job exists, retrieve the data, and write results to the shared dictionaries (`self.jobs` and `self.results`) without synchronization. This can lead to "Check-Then-Act" errors (where two threads process the same job) or data corruption.

To fix this, we need to use a `threading.Lock` to ensure that access to the shared state is atomic. We should also optimize the locking strategy: we only need to hold the lock while checking/removing the job and storing the result. The actual processing (which might be slow) should happen outside the lock to allow other threads to proceed.

Here is the complete fixed implementation:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        # Initialize a lock to manage thread safety
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        # Lock to ensure dictionary modification is atomic
        with self.lock:
            self.jobs[job_id] = data
        return job_id

    def process_job(self, job_id, processor):
        with self.lock:
            # Check if job exists
            if job_id not in self.jobs:
                return False
            
            # Retrieve data and immediately remove it from the queue.
            # This ensures that only one thread can process this specific job_id.
            data = self.jobs[job_id]
            del self.jobs[job_id]
        
        # Process the data outside the lock.
        # This is important for performance; holding the lock during
        # potentially long-running processing would block other threads.
        try:
            result = processor(data)
        except Exception:
            # Optional: Handle processor errors. 
            # In the original code, an exception here would crash the thread 
            # but leave the job deleted.
            return False

        with self.lock:
            # Lock again to safely write the result
            self.results[job_id] = result
            
        return True

    def get_result(self, job_id):
        # Lock to ensure we read a consistent state
        with self.lock:
            return self.results.get(job_id)
```

### Key Changes Made:
1.  **Added `self.lock = threading.Lock()`**: A lock object is created in the constructor to synchronize access.
2.  **Protected `add_job`**: The assignment to `self.jobs` is wrapped in a lock.
3.  **Protected Critical Section in `process_job`**:
    *   The check for existence (`if job_id not in self.jobs`), the retrieval of data, and the deletion of the job (`del self.jobs[job_id]`) are now performed inside a `with self.lock:` block. This prevents two threads from picking the same job simultaneously.
    *   The `processor(data)` call is moved **outside** the lock. This is a best practice to prevent holding the lock while performing work, which would serialize all job processing and reduce concurrency.
    *   The write to `self.results` is protected by the lock again.
4.  **Protected `get_result`**: The read from `self.results` is wrapped in a lock for consistency.