Cross check, double check, and learn by trial and error.Data Science roles are some of the most important jobs in any company. With computer programming, use AI's as much as possible to double check your work. I would have benefited from learning that in person. I hit a wall when I started learning inferential statistics. No one really needs to reinvent the wheel. Usually the queries are built by someone else and I've had to tweak a few things. I reference Chegg Q/A's watch video tutorials, and do query exercises to keep my knowledge sharp. C-Suites love hearing that, especially simplified. Where we started, where we are now, and where can go. What's most important in this spot is to be able to tell a story with the data. ![]() Then you can make rows, columns, graphics, that visualize your data. You need a data source (an excel file most likely) and upload it to the dashboard software. Power BI and Tableau are very fun to play around with. Most things in excel are easily self-teachable - pivot tables, dashboards, graphs, etc. The company had dealt with selfish, information hoarding gremlins before. I was chosen not by my technical skillset but because of by my emphasis on team-work during the interview. Lots of backwards data management, done with not the best practices.Īn unrelated degree with less than a year of self-taught experience = $70k. And thank goodness because this job is tough. The director said that it didn't matter if someone had skills or not, just that they had a willingness to learn. ![]() That's what ultimately got me the job - not my technical skills or lack of thereof. After the interview, I pursued the job with a follow up email, which allowed a follow up interview with the other team member where I pressed the importance of team-work and communicating. He didn't lowball me or let disqualify myself. When the director asked me what my desired salary was, I fumbled around and said something along the lines of $65K but no less than $60k." Then I asked him what to look at my resume, judge the contents, and tell me what my starting salary ought to be. With an unrelated degree and less than a year of self-taught experience, I landed my first data analyst job in healthcare. Soft skills are more important than most people think.Ģ. I interview analyst candidates regularly in my current role and you'd be surprised at how many candidates get turned away bc they don't communicate well or seem like they'd be a pain to work with.ġ. I can communicate a technical or complex idea to a "lay person". ![]() The biggest things that have helped me surpass some of my peers are soft skills. I've worked with lots of people who are more technically skilled than I am. There are definitely some cons to changing jobs often, and it's not the only way to gain more skills and better pay, but it's what worked for me.īut honestly I'd say my technical skills are fairly average. Changing jobs and analytics stacks so much has also forced me to be able to learn and apply things quickly, as well as be super comfortable with analytics fundamentals. This has been really helpful for me in interviewing and landing new higher paying gigs. I can also talk about applying it to various parts of a business, from marketing to finance I've done a bit of it all. When my job at the time wouldnt match the pay or title increase I took the other job.īc of how frequently I've changed jobs I've got experience with a large range of RDBMS, etl, and data viz software, as well as some light data engineering work. My transition from analyst to sr analyst happened because I saw a senior role open at another company and applied for it and got it. All but the most recent job change was intended (got laid off in April due to covid, had a new job by the end of June). Always with an analyst or sr analyst title and doing similar work but with different software and different businesses. I've changed jobs about once every 2 years. ![]() It's a great stepping stone to director positions where salaries are higher. Some managers may make less, but this range probably captures most people. You probably need closer to 10 years of experience to climb higher into six figures. This is a great way to make a lot of money without having direct reports. I don't think these titles are super common but they certainly exist. But definitely possible to make a solid six figure income with enough experience. Analysts probably fall somewhere between 80-90k. Analyst or 3-5 years experience: $75-100k If you're coming from an adjacent field like engineering, you may be towards the top of this range or even exceeding it. This include college grads (undergraduate and masters) and people transitioning into the analytics field. Do you agree? Early career, 0-3 years experience: $50-75k This is my intuitive breakdown of what analysts can expect to make in 2021.
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