Working Nomads’ Post

After going through long lists of Skill Requirements asked by Recruiters, I was actually wondering what all is primarily required as an *Entry Level Data Analyst*. Off course, one can not be a master of all tools and applications out there in the market (atleast as an Entry Level professional) nevertheless jobs these days ask for proficiency in specific tools based on comfort of their use or may be for sync with other members of organization. I request you all to comment with the MUST HAVE SET OF SKILLS at Entry Level and what sort of Experience is expected from such an individual who is trying to secure the very first job. #DataAnalyst #EntryLevelDAJobs #DASkillSEt #RemoteJobs

Tech stacks change How you solve business problems won't Get good at doing the latter → Truly understand the problem → Ask questions → Figure it out → Rinse and repeat This is what they call experience And this is what companies want to hire -- Notice how it's not "years of experience" That's because you can create your own experience before you are a Data Analyst Solve problems/questions with your projects

💡 Tip of the day for Data professionals looking to land a new role 💡 If you want to stand out to recruiters and have worked in a consultancy role as a Data Engineer, Data Analyst etc.. Update the role title to include the role, e.g. "Data Engineer Consultant" When recruiters search for candidates, often we have "years of experience" requirements from our clients. If you worked at a consultancy as a Data professional for X amount of years, but your title for that role is "Consultant at X company", LinkedIn will not include that time as experience in the role, making it harder for recruiters to find you. I have seen a lot of candidates whose experience reflects as much less than it is in reality due to simply not specifying their role at a consultancy in their job title. On a side note, if you are looking for B2B work as a Data Engineer to work fully remotely within the EU, DM me, lots of roles available!

I am trying to find balance between two post themes: * For a data analyst the job market is tight, and many people are looking for work. * People are unwilling to work in positions that require them to go to the office. Is it fair to employers for someone to want a job and also only be willing to take said job if it is remote? For me if the difference between getting a position and not getting a position is going to the office. I hope my office has a nice view. Is this a bad perspective? #JobMarket #RemoteWork #DataAnalyst #WorkLifeBalance #CareerAdvice #NiceView

A lot of job seekers find jobs on LinkedIn using the traditional search job feature . Some are unaware of the advanced Boolean search option Not every job will make it to LinkedIn Jobs a lot will end up as posts and comments on LinkedIn How can you find them? By using certain search keywords like AND, OR and NOT For instance you are looking for a remote data analyst role just input this in the search bar" data analyst" AND "remote" click on posts, click on the most recent(24hrs) and you will see the posts looking for data analyst if it is two roles you are looking for use the OR keyword "data analyst" OR "data scientist" click on posts, click on the most recent(24hrs) Use the same method for the NOT keyword when you want to see only a specific keyword and not anything related to it example "Data analyst" NOT "Data Scientist" Have a splendid week #jobseekers #HR #Linkeldnadvancedsearch

If I was looking for a data analyst job, I’d do the following: 1) Comment on 10-15 posts a day on recruiters' and data creators' posts on LinkedIn. 2) Apply to 5 jobs a day, tailoring each application to the job description. 3) Create 12 data projects because more is better. 4) Pay a million dollars for LinkedIn Premium because you can only send a few InMails on a networking platform. 5) Mass apply to 100 jobs a day. 6) Not ask people for referrals because you’re afraid of people ignoring or rejecting your message. 7) Cry. If you follow this roadmap, you’ll be in good hands!!

Don't feel ready to apply for Data Analyst jobs? Still build a portfolio. Why? First... Each project you build and add to your portfolio get you in the rhythm of the day-to-day job. It's never too early to start getting that experience. Next... As you go through building those projects, there will be knowledge gaps that appear. This is the most efficient way to target your learning and make sure you get to where you want to, fast. Finally... The truth is, you won't ever feel 100% ready. Don't aim to meet every requirement on a job description. If you tick off 70%, you're in a good place. The benefit of building a portfolio as you go means when you decide to start applying, you then don't have to go about building a portfolio from scratch. All you need to do is clean up your existing portfolio and you're ready to go.

The average data analyst makes about $87K. (Keep in mind, entry-level will always be less). This is the figure I came up with when sourcing the average from many reputable career websites like Glassdoor, ZipRecruiter, and Interview Query. The average is not $200K. It's not even $100K. But many factors influence salary. Here are a few: 1. Experience    ↳ This is true for any career path 2. Industry    ↳ People in tech and finance often make more. 3. Location    ↳ NYC, San Fran, and Seattle are home to big orgs. A lot of "Gurus" will make big promises. They're predators looking for likes and course sales. Data is a great career, but let's be realistic. And honestly, $87K is still fantastic. ___ ✌️ What do you think? Did I get it right? ♻️ Repost if you found this helpful.