From a group of words in a column, separate into a different list if a particular word appears

Question

I have a dataframe with 2 columns

1. 'job_title' (filled with all the possible job titles)
2. 'profile_type' (empty)

Conditions:

s1 = pd.Series(df['job_title'])

#checking if the job title contains any of the following conditions

condition1 = s1.str.contains('Head|VP|COO|CEO|CMO|CLO|Chief|Partner|Founder|Owner|CIO|CTO|President|Leaders', flags=re.IGNORECASE, regex=True)

condition2 = s1.str.contains('Senior|Consultant|Manager|Learning|Training|Talent|HR|Human Resources|Consultant|L&D|Lead', flags=re.IGNORECASE, regex=True)

Query:

if condition1.any() == True:
    df_new['profile_type'] == 'Decision Maker'
elif condition2.any() == True:
    df_new['profile_type'] == 'Key Influencer'
else:
    df_new['profile_type'] == 'Influencer'

Could someone tell me what is incorrect in this code as it does not return anything. In the output, the profile type is still empty.

I have also tried the below code

data_dm = pd.Series(['Head', 'VP', 'COO' 'CEO', 'CMO','CLO', 'Chief', 'Partner', 'Founder', 'Owner', 'CIO', 'CTO', 'President', 'Leaders'])

data_ki = pd.Series(['Senior', 'Consultant', 'Manager', 'Learning', 'Training', 'Talent', 'HR', 'Human Resources', 'Consultant', 'L&D', 'Lead'])
    

def condition(x):
    if x==data_dm.all():
        return "Decision Maker"
    elif x==data_ki.all():
        return "Key Influencer"
    else:
        return 'Influencer'

df_new['profile_type'] = df_new['job_title'].apply(condition)

This returns only the value in the 'else' condition. The column profile_type only has the value 'Influencer'

I want the column named 'profile_type' to be filled with 'Decision maker', 'Key Influencer' or 'Influencer' based on the job titles.

Expected Output:

Output:

        job_title                         profile_type
0   -   
1   English trainer                       Influencer
2   Learning and Development Specialist   Key Influencer
3   Director of Training                  Key Influencer
4   Director of Training                  Key Influencer
5   CEO                               Decision Maker
6   facilitator                       Influencer
7   Talent Development Partner        Influencer
8   L&D                               Key Influencer
9   L&D                               Key Influencer

Is there any other method that I can use or try?

Any help is appreciated. Thanks in advance.