def METHOD_NAME(self, request, job_id):
    """
    GET /api/user/v1/skill_level/{job_id}/
    """
    # get top categories for the given job
    job_skill_categories = get_top_skill_categories_for_job(job_id)
    if not job_skill_categories:
        return Response(
            status=status.HTTP_404_NOT_FOUND,
            data={'message': "The job id doesn't exist, enter a valid job id."}
        )
    # assign scores for every skill request user has learned
    top_categories = deepcopy(job_skill_categories['skill_categories'])
    user_category_scores = get_learner_skill_levels(
        user=request.user,
        top_categories=top_categories,
    )
    # repeat the same logic for 100 job holder users in our system
    job_holder_usernames = get_job_holder_usernames(job_id)
    users = User.objects.filter(username__in=job_holder_usernames['usernames'])
    # edx_avg_score should only be calculated if users count is greater than 5, else skip it.
    if len(users) > 5:
        # To save all the users' scores against every category to calculate average score
        category_user_scores_map = defaultdict(list)
        for user in users:
            categories = deepcopy(job_skill_categories['skill_categories'])
            categories_with_scores = get_learner_skill_levels(
                user=user,
                top_categories=categories,
            )
            update_category_user_scores_map(categories_with_scores, category_user_scores_map)
        update_edx_average_score(user_category_scores, category_user_scores_map)
    job_skill_categories['skill_categories'] = user_category_scores
    return Response(job_skill_categories)