In June, we organized our second workshop to navigate our participants through the most popular career social media platform, LinkedIn. Katja Wittforth, lead data scientist at Silo, created a ChatGPT tool called “Resume Fairy,” which helps with building a resume. Elizaveta Gandhi, recruiter at Quisitive, gave advice on how to build LinkedIn profiles and shared insights on the recruitment process. Katerina Presnetsova, QA Leader at Meta, shared her journey on how she got an offer from Meta and earned the Top Voice Community Badge on LinkedIn, which made her profile more visible.
“From a recruiter's perspective: What a recruiter sees when they use LinkedIn.”
By Elizaveta Gandhi, a recruiter at Quisitive
Elizaveta Gandhi started our workshop with a resume exercise: “Share your LinkedIn profile with a person next to you, and set a timer for 15 seconds. In these 15 seconds, try to gather as much information as you can about the person. Scan the resume, then turn to your partner and tell them the top 3–5 things you remember from their profile.”
Then, our speakers discussed with participants what caught their attention first from their partners’ profiles. This exercise was the kick-off to show how recruiters see LinkedIn profiles when they are hiring; they take only about 10-15 seconds to look at your resume or LinkedIn profile.
Elizaveta, with her extensive experience in recruitment from Silicon Valley, shared her tips and insights:
● LinkedIn will show you only selected job postings, so the best way to find out about job opportunities is to go directly to companies’ websites.
● Don’t make vague headlines like “he is making a better world at Meta.” What does that mean exactly? Be more specific. Add your actual position and use keywords relevant to the positions you are applying for.
● “Open to work” is a beneficial filter on LinkedIn. There are different opinions about it, but if recruiters need to find someone for a position quickly, they will use this filter to directly reach out to available people.
● Referrals are important: “If someone puts a referral, we will look at this person first.” Try to network a lot and possibly get referrals.
● Remember knockout questions like “Do you have valid work authorization?” or “Do you absolutely have to have special skills like…?”
● Diversify your job search, for example, by reaching out to agencies and sending your resume.
● Talk about your challenges positively and only if it is relevant to the position. Generally, be positive in interviews.
● Follow up with a thank you note and show interest in the job after the interview, regardless of the outcome.
“LinkedIn Profile Visibility”
By Katerina Presnetsova, QA Leader at Meta and
Katja Wittforth, Lead Data Scientist at Silo
Katerina shared her layoff experience and how she rebuilt her LinkedIn profile in a tough market period to secure a job.
She started with her LinkedIn profile and explained to our guests how she worked on each section:
● The headline is your digital business card: your position and accomplishments. Add a personal touch to show your personality.
● The ‘About’ section is a summary of your resume. Who are you? Engage with your professional expertise and skills.
● Be active on LinkedIn, post about your career journey, expertise, and skills. Make reposts, write articles—everything to keep your LinkedIn professionally active.
● The Top Voice Badge gives additional visibility to your profile. Contribute to relevant articles in your area of expertise.
“Clichéd words—that’s how you know it was AI-generated,” Katja said. In her last job, Katja was looking for data analysts and read thousands of resumes. She assumed that many of them were AI-generated due to clichéd words like “seasoned data scientist,” “leverage,” “utilize,” “delve,” “spearheaded,” etc. She strongly suggested making your resume sound like you. As a data scientist, Katja explained that AI is trained on a large corpus of data from the internet, and that is how vast and repetitive the internet is, with many texts based on SEO that are really targeting just keywords. “Basically, large language models predict the next word.” To use AI efficiently, Katja recommended using techniques from prompt engineering to ask AI what you want and how to talk to AI. Details are important; be specific about what you want and how you want it when you ask AI to do tasks. Katja shared the six most useful prompt engineering techniques she uses daily:
👩🎓 Assign a role -"you are a writing assistant …"
📝 Describe what you are trying to write about, e.g. an "about me" page
⚙️ Describe your style in detail and be specific about how you want to sound.
🚫 Add "banned" words, say "never ever use those words: delve, leverage, …."
📚 Give examples
🔁 Iterate on results in a conversational thread - ChatGPT has a thread memory
Do you want to know more about LinkedIn brand building? Here is the full recording of the event:
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