Analytics jobs: where, when and how to find your dream job
The dynamism of global processes, the development of the information society direct special attention to ensuring data-based decision-making.
But what does it take to become an analytics specialist? What are the skills, qualifications and expectations for this role? How much do analytics specialists earn and where do they work? When is the best time to look for an analytics job? These are some of the questions I will try to answer in this article, using a real data set of more than 4,000 job advertisements in the analytics sector.
Data source
This analysis is based on the Oleh Dubetcky Analyst Job Postings [Pay, Skills, Benefits] dataset of 4,061 job postings with various job titles.
The dataset contains «Data Analyst» 28.73% (1167) of the total amount of data. Other categories are presented with the following percentages and numbers:
Business Analyst: 28.29% (1149)
Data Engineer: 12.33% (501)
IT Analyst: 9.01% (366)
Data Scientist: 6.91% (281)
Trade Analyst: 5.49% (223)
Web Analyst: 3.29% (134)
Financial Analyst: 2.38% (97)
Media Analyst: 1.05% (43)
Cybersport Analyst: 0.96% (39)
Cyber Analyst: 0.64% (26)
Mobile Analyst: 0.64% (26)
GIS Analyst: 0.22% (9)
What are the most common skills?
import seaborn as sns
from matplotlib import pyplot as plt
from collections import Counter
def plot_top_non_stopwords_barchart(text):
new= text.str.split()
new=new.values.tolist()
corpus=[word for i in new for word in i]
counter=Counter(corpus)
most=counter.most_common()
x, y=[], []
for word,count in most[:150]:
if (word not in stop_words):
x.append(word)
y.append(count)
sns.barplot(x=y,y=x)
plot_top_non_stopwords_barchart(df_analyst['description'])
The chart shows common keywords in job descriptions. The most common term is “analysis” (2,297 times), followed by “development” (1,305 times), “sql” (1,139 times), “implementation” (1,055 times) and “business processes” (916 times). This indicates that analytics jobs often require skills in the analysis, development and support of business process systems.
What work schedule do you offer?
df_analyst.groupby(['schedule_type'])['schedule_type'].count()
The table shows the types of work schedules. Full-time is the most common, with 3,575 offers.
When is the best time to look for a job?
df_analyst['postdate'] = pd.to_datetime(df_analyst['postdate'], format='%Y-%m-%d')
x = df_analyst['postdate'].groupby(df_analyst.postdate.dt.month).agg('count')
x.plot(kind = 'bar')
The chart shows vacancies by month, with the most in January (506), followed by February (614) and March (597). This indicates that most vacancies occur in the first quarter of the year.
Which company offers more opportunities?
c = df_analyst.groupby(['company_name'])['company_name'].size().nlargest(20)
c.plot(kind = 'bar')
The chart shows the most popular companies that post jobs. PrivatBank leads with 88 vacancies, followed by EvoPlay (42), Eva (35) and MHP (32). This tells us that large companies tend to be actively hiring for analytics positions.
Where are most of the jobs?
x = df_analyst.groupby(['location'])['location'].size().nlargest(20)
x.plot(kind = 'bar')
The diagram shows vacancies by city of Ukraine. Kyiv has the most (2988), followed by Dnipro (269), Lviv (198), Odesa (103) and Kharkiv (81). This helps determine where to find analytics jobs.
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