An impressive machine learning resume should contain a professional experience section that effectively showcases career highlights. Whether you worked on data mining or statistical analysis, this section should reflect your contribution and achievements.
An impressive ML Resume should contain a professional experience section that effectively showcases career highlights.
Whether you worked on data mining or statistical analysis, this section should reflect your contribution and achievements.
Here is how you can master this section:
One liner points: When you are writing your resume, you need to make sure that while adding information, you do not create a blunder and mess up the readability. You can avoid this by constructing one-liner bullet points.
Subheadings: For 3-4 statements, create relevant subheadings to efficiently showcase your contribution. For example, predictive analysis & data visualization, regression modeling & statistical analysis,.
Write your projects
For a tech professional, projects are one of the most important aspects to tackle in a resume.
However, most individuals end up writing all the steps involved in each project and stretching the resume to 5-6 pages.
Here are some pointers that will help you understand how to write projects in your resume:
Tech stack: Include all the methodologies you have used in all your projects.
Areas of expertise
In today’s market, recruiters receive thousands of applications for a job. Most companies have even started using personality testing tools to acquire talent.
However, for a tech professional, one of the most important factors to consider is the relevance of their skills.
Recruiters look for skills that can link the candidate to the job requirements.
So you need to make sure that your resume has skills that are relevant to the target profile.
Here is how you can tackle this:
Key Skills: Create a section for your non-technical skills that reflect your core competencies. For example, data visualization, factor analysis, data mining,. Additionally, you can also use the subheadings in the professional experience section as skills.
Technical skills: Create another section to include all the tools and methodologies you are familiar with. For example, Python, MapReduce, Scikit-learn,.
Write a professional summary
As this one famous saying goes “first impressions last”. It is the same with a resume. A professional summary is the first thing that recruiters notice. Hence, it is important to make sure that you make it perfect.
Though it is ideal to make a summary about yourself, you need to write it in a way that resonates with job requirements.
Check the following example of a professional summary:
4+ years experienced Certified Machine Learning Professional with expertise in deploying Artificial Intelligence concepts like EDA to analyze datasets. Adept at deploying project management skills to ensure timely execution of key deliverables, and developing algorithms to streamline business processes.
To pick the key highlights of your professional career, you should write the summary at the very end.
Further, here are a few things to avoid while writing a summary:
Ensure that the summary is free of any first and second person pronoun usage.
Begin sentences with proficient in, adept at, skilled in,.
Write an objective statement if you have less than 3 years of experience.
Include relevant certifications
Most tech job profiles require professionals to use their expertise immediately and in most cases real-world execution of these skills is required, making certification incredibly important.
Certifications also help bridge the skills gap between the application and target profile. Hence, it is important to include certifications in a resume.
Here is how you can write your certificates:
Machine Learning & Artificial Intelligence Certification | Harvard Upskilling Centre | Jan ‘20
Linear Programming | Clustering | Logistic Regression | Automation
Tip: Include key modules that are relevant to the target job profile.
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