Transitioning careers or entering the job market can be a daunting task, but with a data-driven approach, you can streamline your preparation and increase your chances of success. In this article, I provide practical steps to help one identify the skills in demand, prioritise your learning, and make yourself visible to potential employers. Included is also a prompt that can easily be used with for example OpenAI’s ChatGPT or Google’s Gemini to easily conduct the analysis. Naturally other analysis methods can be applied. While the examples are largely tailored to a career in Data Analysis, the underlying steps are applicable to other fields as well.
Step 1: Identify the skills needed for your target career
To begin, it’s crucial to identify the skills that are most sought after by employers. As a Data Analyst, I have often received questions as to whether to study python or R, while I can give my opinion based on my workplace, it is beneficial to leverage data to guide the decision. Start by analysing job boards such as Jobylon or LinkedIn Jobs, and search for positions related to your desired career. This will help you discover the most in-demand skills in your desired location. Filter by location if that is a factor.
Step 2: Prioritise skills based on market trends, benefits, and location
Now that you have a list of skills, it’s time to prioritise them based on various factors. Start by analysing the correlation between specific skills and advertised benefits or salaries. This will help you identify skills associated with higher earning potential, aligning your learning with your career goals. Additionally, analyse the growth trends of these skills over time to stay ahead of the curve and focus on those with increasing demand.
Step 3: Acquire skills and make them visible
Once you have prioritised the skills, it’s time to acquire them and make your expertise visible. Search for online courses, tutorials, and bootcamps that cater to these specific skills on platforms like Udemy, Coursera, edX, or university websites. Filter the learning resources based on your current skill level, ensuring you find materials suitable for beginners, intermediate learners, or advanced professionals.
To showcase the real-world applicability of your skills, consider engaging in projects with non-profit organisations or participating in competitions. These experiences not only help you grow your skills but also demonstrate a social impact. Additionally, leverage hobby projects, summer jobs, or internships to gain practical experience.
Step 4: Tailor your CV, resume, and LinkedIn profile
Now that you have acquired the desired skills and gained some practical experience, it’s time to tailor your CV, resume, and LinkedIn profile to highlight your expertise. Incorporate the keywords you discovered during the analysis of job postings into your skills, experience, summary, and header sections. This will make your profile more relevant and attractive to potential employers.
Step 5: Build your network based on your findings
They say your network is your net worth. Leverage the findings from your analysis to build a relevant professional network. Perform a LinkedIn search based on the identified keywords and connect or follow individuals who are active in those areas. Follow companies related to your desired field and participate in skill-related events organised by those companies. Building a strong network, regardless of the country you are in, can open doors to opportunities and valuable connections.
Find below an example of a process that you can adapt for your own use.
In summary, while a data-driven approach is a valuable tool in building your career path, it’s important to consider your personal interests, career goals, and learning preferences as well. Combine the insights gained from data analysis with your passions to make informed decisions about your learning journey. With the right skills, a tailored profile, and a strong network, you’ll be well-prepared to pursue your dream job and achieve professional success.
Process:
1.Create an Excel with job descriptions in one column. Collect as many relevant positions as possible.
2.Enter the below prompt in ChatGPT or Gemini or another tool. I would recommend trying this on multiple platforms as for instance ChatGPT provides insights based on available data up until 2021. For Tech jobs at least, the job market changes fast. Therefore, it’s essential to supplement this analysis with up-to-date information and stay informed about the latest trends.
Prompt: “Please analyse the keywords from the job posts that are shared below and provide insights on their frequency, benefit correlation, and market trends for a career in [Data Analytics]
First, Identify the most frequently occurring keywords in these job posts related to [Data Analytics] and provide a ranked list of these keywords based on their frequency of occurrence.
Secondly, analyse the correlation between the specific skill keywords and the benefits of the job posts. Identify keywords that show a strong positive correlation with higher salaries in the [Data Analytics] market. Provide also insights into the skills or keywords that are associated with higher earning potential in [Data Analytics].
Thirdly, analyse the growth trends of specific skills or keywords over time in [Europe]. Identify skills or keywords that have seen a significant increase in demand over the past [3 years]. Provide insights into emerging skills or keywords that are in high demand and can give professionals a competitive edge in [Data Analytics].
Lastly, Please present the results in an organised manner, including the frequency-ranked list of keywords, a summary of benefit correlations, and an analysis of market trends. Additionally, if there are any notable findings or recommendations based on the analysis, please include those as well.
[Attached are the job descriptions in csv file/Below are the job descriptions]”
Below are screenshots of sample results from Google’s Gemini with the above prompt.
Screenshot of sample results from ChatGPT
