Today, we’ll dive deeper into the content of your resume and focus on two important elements:
- Creation of a clear persona
How did you craft your technical “persona”?
What is the technical “persona” you are demonstrating on your resume?
Your technical persona is a combination of your work scope, skill level, and experience coverage. How are they demonstrated?
It’s the combination of the following:
The bullet points under your most recent role x 50% + the bullet points for your previous roles x 30% + your education x 20%.
While the weighting of these components may vary from hiring manager to hiring manager, it’s generally agreed that the most recent role carries the heaviest weight.
Using my most recent MLE opening as an example, the job description (JD) describes projects you might work on as:
“Projects can range from working on a wide-variety of machine learning and/or deep learning (DL) problems, e.g. segmentation/clustering, propensity modeling, classification, forecasting and prediction, fraud/anomaly detection, search and ranking, collaborative filtering/recommendation, natural language processing, and computer vision.”
As we’ve discussed before, you’d want to construct your bullet points in a way that has the most relevant keywords, and in the right proportion.
The above JD tells you that I need an MLE who can work on a range of machine learning and deep learning problems, such as segmentation/clustering, classification, and forecasting, etc. If you construct your bullet points by relevant projects, prioritize the projects related to these topics.
The order in the JD also matters. Often, the most important projects are listed first, while the ones listed at the end are relatively less of a priority. However, there are exceptions. For instance, if you have expertise in applying deep learning methods to NLP or CV, and these skills are relevant to understanding customer behavior, it’s fine to list them at the top.