Curriculum Vitae for Data Scientists

Applying for a data scientist job offer? Tired of writing the same old curriculum vitae?

Why not showing your data visualization skills directly in your application?

Generate Data

Instead of pressing your data about education, employment and skills in a word-like document, put it in tables instead.

E.g. use open office to create and edit csv-files

For this example I’ve created two files: skills.csv and jobs.csv

Work experience

import matplotlib.pyplot as plt
import pandas as pd 

jobs = pd.read_csv('./jobs.csv')
jobs
 Index Employer Duration / Month
 0 Landestheater Detmold 18
 1 Harman Becker 48
 2 mgm technology partners 19
 3 self-employed 17
 4 e.solutions 70
pie = jobs.plot.pie(y='Duration / Month', labels=None, autopct='%1.0f%%')
plt.title('Work experience', weight='bold', size=14)
plt.legend(labels=jobs['Employer'], title="Employers", 
           bbox_to_anchor=(1.2, 0.5), loc="center right", 
           fontsize=10, 
           bbox_transform=plt.gcf().transFigure)
plt.subplots_adjust(left=0.0, bottom=0.1, right=0.85)
plt.gca().axis("equal")
plt.show()
plt.clf()
plt.close()

 

Skill-Competency-Matrix

The idea of the skill-compentency-matrix is to show your competence in your skills in a two-dimensional plot: how long have you been practising these skills and how confident are you in them.

skills = pd.read_csv('./skills.csv')
skills

 

Skill Type Number of month practiced Competency Level
 0 Python Programming Language 36 92
 1 Java Programming Language 25 74
 2 C++ Programming Language 48 56
 3 JavaScript Programming Language 36 76
 4 jQuery Framework 32 81
 5 HTML Programming Language 40 95
 6 CSS Programming Language 24 63
 7 KnockoutJS Framework 6 50
 8 SQL Programming Language 43 78
 9 Jira Tool 60 88
 10 Confluence Tool 56 75
 11 PyCharm Tool 34 86
 12 Eclipse Tool 66 68
 13 Visual Studio Tool 50 45
 14 Polarion QA Tool 36 74
 15 Selenium Framework 32 83
 16 jUnit Framework 25 66
 17 Flask Framework 33 94
 18 Vector CANoe Tool 18 57
 19 scikit-learn Framework 5 15
 20 Numpy Framework 6 42
 21 Pandas Framework 6 25
 22 matplotlib Framework 6 20
 23 openCV Framework 2 10
groups = ["Programming Language", "Framework", "Tool"]
fig, ax = plt.subplots()
plt.style.use('ggplot')
fig.set_size_inches(10, 8)

for group in groups:
    skill = skills[skills.Type == group]
    ax.plot(skill['Number of month practiced'], 
    skill['Competency Level'], marker='o', linestyle='', ms=12, label=group)
    for i, txt in enumerate(skill.Skill):
        ax.annotate(txt, (skill['Number of month practiced'].iat[i],
        skill['Competency Level'].iat[i]), 
        xytext=(10,-5), 
        textcoords='offset points',)
ax.legend()
ax.set_xlim(0, 100)
plt.xlabel('Number of month practiced')
plt.ylabel('Competency Level')
plt.title("Skill Competency Matrix")
plt.show()

The plot shows a nice overview of my skills acquired over the years:

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