How to Grad & Beyond with Betul

When you are graduating soon and starting to look for jobs, you might end up in a situation where you have too many options and don’t know which job to apply for. Often, each job family has multiple job titles that look similar and you may not know what differentiates between them. How do you proceed in this situation and set a direction for yourself?

The first step is to study and understand yourself. To do this, first ask yourself:

•What makes me feel at a natural state such that I can lose myself in it for hours?

•What can I solve more quickly than other people?

These questions will guide you to a general career path. For example, I was asking these questions to myself when I was finishing up my PhD in Linguistics. I was obviously interested in languages, but when I asked these questions, it became apparent to me that I loved data – any kind of data and not just language data. I loved seeing patterns in data and putting these patterns in a system (i.e. ontology). This allowed me to look for jobs in a broader job family that is not restricted to language-related jobs, which made it easier to move into employment more quickly.

Once you have an idea about your general career path, now is the time to find a list of related jobs (finding a flowchart focused on your specific job family could be helpful here). In my case, that would be anything with ‘data’ (or language) in it and write down their primary focus. For a data-focused job search, this step could look something like this:

Data Engineer – Data Ingestion & Building Pipelines

Data Scientist – Data Exploration, Research & LLMs (requires strong analytical skills)

Data Analyst – Data Exploration, Visualizations & Communication

Data Architect – Data Infrastructure Design, Business Vocabulary Development

…

You can also extract information about different roles in your general career paths by reading job descriptions, specifically ‘What you’ll be doing/Job Responsibilities’ section. Here, you can see what specifically differentiates the specific job titles and how they are similar. For example, a Data Analyst and a Data Scientist both focus on data exploration and you will likely see this in job descriptions (they will have a focus on data-driven decision and deriving insights from data). However, a Data Analyst will more likely focus on visualizing and communicating the explored data patterns while a Data Scientist will focus more on research questions/findings and working with LLM models using the explored data.

Once you have an idea about the distinctions within jobs in your field, now you can find the best-matching job with your answer to the questions above. Congrats, you found the first job on your career path!

Now you know where you want to be headed in your career. But the process doesn’t stop there. You need to make sure you have the skills required and know the tools needed to even apply for that job. How do you go about this part of the process? That will be in my next post!

(If you want to chat about the job process in more detail, feel free to book a free consultation with me using the links at the top of this page. If not, see you in the next post!)