data analyst 2023 reddit - Brave Search

How to become a Data Analyst in 2023

reddit.com › r › dataanalysis › comments › 11g7kuv › how_to_become_a_data_analyst_in_2023

This gets asked a few times a week. You can use the search function to see what others have said That being said - I would just blast as many resumes as she can. The market is tight and “entry level” has never really existed for this field Good luck! Answer from Deleted User on reddit.com

reddit.com › r/dataanalysis › how to become a data analyst in 2023

r/dataanalysis on Reddit: How to become a Data Analyst in 2023

March 2, 2023 -

Hi Reddit,

I'm not 100% sure this is the best place for this question but thought it'd be worth a shot.

My wife has been looking for a Data Analyst position for several months. She does not have prior experience in any tech roles and is transitioning from being a High School math teacher.

I'm sure many of you can imagine how difficult it is to switch careers, and I'd like to see if anyone in the industry has some advice on how someone with no prior experience can maximize their chances of getting an interview for an Associate Data Analyst position.

Below are some of the things she has tried thus far:

Obtained a Master's Degree in Statistics
Worked on basic prjects for her portfolio in Codecademy/Github
Taken courses on things like SQL, Python, Tableau
Tailored her Resume to include keywords recruiters would look for based on the average Data Analyst position
Set up alerts for Data Analyst on popular sites (Indeed, LinkedIn, Glassdoor, etc.)
Attempted to leverage personal connections with tech friends
Attended job fairs

I'm biased of course but I am 100% certain she is going to be able to knock this out of the park if she can just get some interviews. Does anyone have a suggestion on something we may not have thought of? How can she stand out to recruiters without having X years of experience in the field already?

This gets asked a few times a week. You can use the search function to see what others have said That being said - I would just blast as many resumes as she can. The market is tight and “entry level” has never really existed for this field Good luck!

Given her masters in statistics, she should also apply for Data Scientist roles. How long has she been applying? Does she also have a LinkedIn profile that’s optimized? Also what country are you in?

reddit.com › r/dataanalysis › is switching to data analytics a bad idea in 2023?

r/dataanalysis on Reddit: Is switching to data analytics a bad idea in 2023?

January 28, 2023 -

I was laid off from my job as an attorney back in November. Prior to the lay off, I considered switching to a data analysis/programming/coding job since the legal job market is oversaturated, and now seems like a perfect time to transition since I can focus on learning a new skill.

However, I’m worried the switch to tech may not pan out though due to the recent tech layoffs, and I have had trouble finding another attorney job. I’ve been applying to jobs daily since the lay off, and I’ve been teaching myself how to code. I plan to start a boot camp once I’ve gotten a little more proficient at coding.

Is it a bad idea to switch to tech in 2023? Any advice is welcome.

I’m doing basically exactly what you’re considering right now. I have 10 years high level sales experience and was laid off at the end of the year. I was initially interviewing for other sales roles but stopped applying for them entirely and focused on completing the Google course, learning SQL and Tableau, and putting a portfolio together.

I got through the Google course in about 2 weeks, spending about 8 hours a day watching videos, taking notes, studying. I was learning more SQL on the side through YouTube videos and fully immersed myself by even watching SQL TikTok videos.

Took me about a week to put together a decent portfolio with a couple of Tableau dashboards, a SQL cleaning project in an Azure notebook, and a quick project I did in R for the Google capstone.

I started applying for data analyst jobs Monday last week and haven’t had much luck. I’ve probably submitted 150+ applications and received 2 calls from recruiters from the same recruiting company about 2 different jobs at big companies in the domain my experience is in. Both screenings seemed promising but haven’t heard from any hiring managers yet.

But you know what? When I was applying for sales jobs (where I have experience) it was the same rate.

The one thing keeping me going is - earlier this year I had just started applying to analyst jobs in my domain out of the blue without knowing anything other than Excel. I made it through 3 rounds of interviews and even got to the technical round. I didn’t get that job but I keep reminding myself that if I could get to that round without knowing anything, then I can definitely get to that round now. And when I do get to that round now, I’ll crush it.

My goal is to have a job by my birthday at the end of June. That’s about as long as I can go without a job. At this rate, I’m a bit discouraged but it’s only been a week and I plan to keep at it. I have a hard time believing I won’t find a job in that time span if I continue at the rate at which I’m applying. I’ll re-evaluate in a month or two - at which point I may find some form of income to get me by.

I say go for it if you have the income to sustain for a long period of time.

How many years of experience do you have? Also which country are you looking for a job in? What's the level of programming you've done before?

It would be a bit difficult to land a job in tech right away with no background given the current situation of the market. But it's not impossible. If you're looking to get employed quickly then it would be better to apply to jobs you have got prior experience into.

reddit.com › r/resumes › expected to graduate in may 2023, 60+ applications to data analytics jobs (data analyst, business analyst, data scientist) and 0 interviews so far, looking for feedbacks

r/resumes on Reddit: Expected to graduate in May 2023, 60+ applications to data analytics jobs (data analyst, business analyst, data scientist) and 0 interviews so far, looking for feedbacks

February 12, 2023 -

Hi everyone, I will be graduating from Master of Statistics in a Canadian university this upcoming May, but I haven't had a job lined up before graduation, and I am starting to get nervous. I have tailored my resume and cover letter to include as many keywords from each job description as possible to pass the ATS, but still no luck. I have had several people from my university's career centre review and fix my resume too, but still no invitations. Some questions in mind:

What are the improvements I could add on my resume?
I wonder if unconscious bias is still a thing, because my surname does not sound like a name from North America, and that is another reason why I did not include my Bachelor information in my resume.
Should I put my skills and certifications at the top, or should the education section be written first?

Here are my suggestions:

Include your Bachelor's degree
You don't need any info under your Master's degree, you can share those details either in a cover letter or an interview.
Remove "expected graduation" and just put "May 2023", hiring managers will understand what this means
I would suggest putting the same amount of bullets under each job description to make things flow better. Can you do two bullets per job? I'll include an example:

Teaching Assistant

Provide support and assistance to individual students and small groups to increase their understanding of difficult materials
Successfully increased test scores by 20%

Math and Physics Tutor

Offered professional tutoring services to wide range of students from Grade 4 - 12
Provided services through a people-first approach with a focus on increasing results and instilling confidence in students

Hopefully those help. Some more suggestions:

I would remove "Canada" after the company name.
Your information in the bottom section of your resume is good but it looks a little too busy. I would recommend spacing them out more. If you need to go onto two pages, go onto two pages.
Under your Data Analyst role, the first point has "automated" twice. I would suggest fixing that sentence.

Overall you're a good candidate for Data Analytics jobs, you have good experience. What I will say is that companies in Canada don't typically hire this far in advance. You aren't graduating for another 4 months. You can still certainly apply, but I wouldn't expect you to get anything that starts in May/June at the beginning of February. I would suggest using this time to research companies you really want to work for and work on getting your foot in the door - go to events they may be hosting, follow them on their social media, sometimes they companies have general recruitment sessions, etc. Then closer to your graduation date, start applying again. Personally, I would start looking again around mid/end of April. You have lots of time. Good luck to you!

Are you authorized to work in Canada, or are you looking for sponsorship? It might not even be unconscious bias based on your name but intentional bias based on your visa status.

reddit.com › r/dataanalysis › megathread: how to get into data analysis questions & resume feedback (august 2023)

r/dataanalysis on Reddit: Megathread: How to Get Into Data Analysis Questions & Resume Feedback (August 2023)

August 3, 2023 -

Welcome to the "How do I get into data analysis?" megathread

August 2023 Edition. A.K.A. Mods Gone ~~Wild~~ On Vacation!

Rather than have 100s of separate posts, each asking for individual help and advice, please post your questions. This thread is for questions asking for individualized career advice:

“How do I get into data analysis?” as a job or career.
“What courses should I take?”
“What certification, course, or training program will help me get a job?”
“How can I improve my resume?”
“Can someone review my portfolio / project / GitHub?”
“Can my degree in …….. get me a job in data analysis?”
“What questions will they ask in an interview?”

Even if you are new here, you too can offer suggestions. So if you are posting for the first time, look at other participants’ questions and try to answer them. It often helps re-frame your own situation by thinking about problems where you are not a central figure in the situation.

For full details and background, please see the announcement on February 1, 2023.

Past threads

This is megathread #6.
Megathread #1 (February 2023): See past questions and answers.
Megathread #2 (March 2023): See past questions and answers.
Megathread #3 (April 2023): See past questions and answers.
Megathread #4 (May 2023): See past questions and answers.
Megathread #5 (June 2023): See past questions and answers.
Megathread #6 (July 2023): You can still visit and comment here! Lots of unanswered questions.

Useful Resources

Check out u/milwted’s excellent post, Want to become an analyst? Start here.
A Wiki and/or FAQ for the subreddit is currently being planned. Please reach out to us via modmail if you’re willing and able to help.

What this doesn't cover

This doesn’t exclude you from making a detailed post about how you got a job doing data analysis. It’s great to have examples of how people have achieved success in the field.

It also does not prevent you from creating a post to share your data and visualization projects. Showing off a project in its final stages is permitted and encouraged.

Need further clarification? Have an idea? Send a message to the team via modmail.

Hi All Social scientist that wants to transition into data analytics. My job currently involves a lot of data analytics, primarily in R, and then presenting that data in report papers/presentations. I am finishing a Masters in Quantitative Social Research over the next 12 months, which will likely include a dissertation using regression techniques. I know people talk about the Google Certificate, but to be honest, I think I am further along in the journey than that certificate is designed for. But I did come across Microsoft's certificates and wondered whether they would be helpful as a) I don't have Power BI experience and b) I don't have cloud-based experience. The ones I was looking at are: Power BI Data Analyst Associate PL-300 Azure Data Fundamentals DP-900 Azure Enterprise Data Analyst Associate DP-500 What do people think about these? Do you think they would be helpful?

Hi, After career plan a did not work, I'm determined to focus on plan b, data analysis. I'm starting to think about my application materials and crafting a narrative of my past experience. My problem is that I'm not feeling very confident about my past experiences and feel like Im not ready even though others say I am. My background is in libraries (Master's in Library Science) and allows me to dive deep when learning about a new domain or industry. I took a database management and maintenance course while in library school which sparked my interest in the first place. I also took a course I'm Metadata and recognize the importance of accuracy naming or describing something. During my first library job I analyzed data about physical collections to determine what should be withdrawn and what could go into storage. My favorite project from this job was something that I initiated with a colleague, which was figuring out which areas grew fastest so that more space could be left for those parts to expand and less space could be left for slower growing areas. The stacks team ended up spending less time constantly shifting which left more time for other projects. I also taught myself how to use a library specific analytics tool in a week because no one else wanted to learn it or had time to do so. I became the point person for that tool. At my next job I used data to help our team make decisions about which subscriptions to cancel, which to add, and which to out right purchase rather than subscribe to annually. Since these experiences I've been teaching myself SQL and I would like to play around in Python. I know a bit of Tableau and navigate Excel well. I've also been teaching myself Power BI although I don't find it as interesting as Tableau, though Power BI is a low cost option for many so i understand the importance. I guess I'm just trying to figure out how to put this into a narrative that would make me attractive to employers and I wonder if industries will look down on my higher ed experience.

reddit.com › r/dataanalysis › data analyst roadmap for 2023

r/dataanalysis on Reddit: Data Analyst roadmap for 2023

April 2, 2023 -

Seeking help with becoming a Data Analyst within 12 months. I plan on taking the Google DA course in April and do a detailed learning on these skills in this order: Excel>SQL>Tableau>Python>building projects. How do I divide my time? What resources can I use to learn?

Its should be: excel > build projects > SQL > build projects > Tableau > build projects etc.. Hate it brake it but you won't be able to do all that within 12 months. Google DA cert will take you about 4/5 months if you're doing it in you're free time. All of the course content is introductory level and you'll need to do further learning once completing it

We have a thread that will answer the questions you seek. https://www.reddit.com/r/dataanalysis/comments/10onhl2/want_to_become_an_analyst_start_here/

reddit.com › r/datascience › i posted for a data analyst, this is what you are competing against

r/datascience on Reddit: I posted for a Data Analyst, this is what you are competing against

May 19, 2023 -

Our org needs a new data analyst, so I wrote up a job description with the skillset I needed and passed it off to our HR director to do what she needed and post it. I didn't put any degree requirement on it, I put responsibilities and real tools the new hire would be expected to work with. It is a remote role. I started looking for the posting, but couldn't find it, so I asked for a copy because my LinkedIn was getting attention indicating it existed somewhere.

I expected this response if I had posted for a Data Scientist role, but I didn't. I posted for a Data Analyst.

She took it down. There were 255 applicants in less than 24 hours. She sifted through half of them, excluded those who weren't already authorized to work in the US and those who didn't show English proficiency through their resume, and then forwarded me 9. I don't know that the 9 was all of the viable candidates that remained, they did seem to be biased to areas we have a footprint in the US, and I had just requested a sample.

Of those 9, 3 were absolutely new to the field. They put a data analytics certificate, but didn't even list which of the languages indicated on the posting they already knew. They didn't list any projects, just their previous work history (which was at best adjacent to the field). I looked up their certificates quickly and then moved on. List your technical skills - I'm not looking for "good attitude, can learn", I want to know how you've gotten yourself started in ways that are relevant to what I need. Your certificate only matters in what it taught you, not that you have it.

I had 4 that were on point. They had the skills I had listed and then a few, and they either had relevant work experience or a history of coursework (online or through universities) that showed they would have a good framework to start from.

Two were overqualified. Their experience was legitimately as data engineers. I assume they actually read the posting, so they remain in consideration, but their skills are beyond the specifics I need. I can't justify paying them more unless I can find ways that benefit the org to use those extra skills. I assume they will drop themselves from consideration when we talk more, so if I were in a time crunch, I would cut them from my list. Wishful thinking on getting a unicorn isn't a good use of my time.

I figured this was an opportunity for some perspective, seeing that we get "what do I need to do to get a role" posts all the time. I don't know what response I would have received if I had region locked this to around our HQ, or if we were offering hybrid or on-site work.

Just to add - I am not accepting resumes through here. I'm also ignoring anyone who finds my or my coworkers' LinkedIns and sends us resumes outside the standard process. I've already seen those happen.

Edit to add: I also considered projects in the "on point" group - they showed they applied the skills.

Update: I checked with HR, the pay was included in the post. To be clear, it was mid-3rd quartile for a Data Analyst position - we weren't posting anything with an amazing rate. It's very possible people submitted without reading the details, especially given the skill mismatches I see. I feel better about it, because I could not have written a more honest description of the role, so they had full information.

Also, 27 resumes were forwarded to me so far. I have sent 10 back for follow up, with another 5 to be written up on my side.

So I guess the obvious takeaway is that there's just a ton of noise to sift through, which has definitely been my experience when reviewing resumes for remote data science positions. But another takeaway is that you got (at least) 4 properly-qualified applicants and another 2 maybe-overqualified applicants from 12 hours' worth of applications. So if you left the posting up for a week, you'd probably get more qualified applicants than you'd ever want to interview, albeit not until after wading through 1000+ obviously unviable ones.

Two were overqualified. Their experience was legitimately as data engineers. I assume they actually read the posting, so they remain in consideration, but their skills are beyond the specifics I need. I can't justify paying them more unless I can find ways that benefit the org to use those extra skills. I assume they will drop themselves from consideration when we talk more, so if I were in a time crunch, I would cut them from my list. Wishful thinking on getting a unicorn isn't a good use of my time. As someone who has been searching for a new gig for 10 months after going to grad school for statistics and 6 years of experience in the field, this is infuriating.

reddit.com › r/analytics › what data job is clearly the "hottest" in 2023/2024?

r/analytics on Reddit: What data job is clearly the "hottest" in 2023/2024?

November 7, 2023 -

Data Engineer hands down!

Agree with Data Engineer being the hottest with major caveats. The entry level the bar is quite high and the pay/skill ratio isn't that good IMO. I'm making 150k as a data analyst manager where I was previously applying for data engineer roles at 100k-120k. Obviously I have the tenure to become manager and this is apples to orange, but what I see in the market after taking the coding tests and questionaires is that, the skill/pay ratio for DE's is very high compared to DA's. As an example, one position for 130k asked for Hadoop, Azure, and AWS knowledge (yes all of it) combined with interfacing across HDFS systems for modeling data. This was supposedly entry level. Another position required needed Snowflake, AWS knowledge on lambda and EC2 .... was only paying 80k. An equivalent analyst with that pay would have just needed Tableau and some basic Sql knowledge. I see the market as too competitive for these roles. Clearly I got my ass kicked by some real talented kids out and maybe I'm just too old to keep up.... but having been in a super hybrid position of DE/DA/DS, I don't think DE should be the goto DA for fresh grads right now because: Too narrow, DE skills don't translate into things like CS jobs. It's not as transferable as Data Analysis skills which can bridge to many roles including management. So if you find you don't like it, it's not easy to tranisition. Requiring a lot of education and upkeep on that education. AWS, GCP, Azure is hot shit now, but who the hell knows what's going to happen to cloud servers. We are already seeing trends to retract expensive cloud servers to on prem. The skill sets change almost yearly. Flexibility. Data analysts have what... 3-4 frameworks we juggle between? Tableau, PBI, Google Analytics looker thing? DE's have to google between Big data tech, snowflake, cloud servers, multiple languages anything from python to databricks etc. Non-Recession proof. If I were a manager with compromised year budget, would I rather retain my DE or DA? Well I worked for an AI company that had exactly this questions and they essentially laid off all DE's except 1. They kept 5-6 Analysts. And this is a company that is tech savvy and they still made this type of decision. This is not to say being a DE isn't a fun job. I loved doing DE tasks and coding ETL pipelines in python. But I feel the market is highly resistant to entry level DE's compared to entry level DA's. Just my 2 cents. I could be biased.

There is no clear defined path to the data job you want. Data Analyst, Business Analyst, Data Engineer, Analyst- these roles all crossover depending on your companies org and needs. Even parts of "data scientist" fall into this amalgamous bucket. A data analyst here might be a data engineer there. What is important, and what will get you interviews and promoted, is the ability to storytell technical information to a non technical (business) audience. Most in this field can do the technical work (SQL, Python/R, Data Viz). If you want to stand out and stay in demend regardless of what your role is called, be able to provide value up the corporate ladder.

reddit.com › r/dataanalysis › google data analytics apprenticeship 2023

r/dataanalysis on Reddit: Google Data Analytics Apprenticeship 2023

April 25, 2023 -

The information on this apprenticeship is so limited so I am taking the initiative to create my own thread having just submitted my application. I will update whenever I get any updates lol but other applicants please feel free to share your experience because we need more info on this great opportunity. So pretty much I signed up for Google alerts so that I wouldn't miss the application deadline but after the crickets from the 2022 apprenticeship I didn't have my hopes up at all. In fact, I was in the process of applying to college for Data Management because I just thought they weren't going to do it this year. But literally yesterday in the middle of my run I got a notification that the application was live. What shocked me the most was that the deadline was to submit before April 25th and if I am not mistaken the application opened April 23rd. So I am assuming they really want to cut down on the number of applicants. This makes sense to me because I didn't even get a rejection letter last year it was just nothing. I am still keeping my hope at a minimum and I believe the salary is a bit smaller but with all the big tech cuts once again it all makes sense. Also, this year I chose to include a cover letter, I know it was stupid of me not too in the first place, just so they could get a better sense of who I was, what my resume was about and why I wanted this apprenticeship. I feel like for those who want to apply to jobs like this it's truly essential to include a cover letter because odds are you aren't a traditional candidate to begin with which is the whole point of opportunities like this so you really want to give them a sense of who you are. Hopefully communication is better this year. Fingers crossed.

Does anyone know when the apprenticeship opens this year again? Im desperately waiting to apply. Please anyone which month again is the applications open for this year? In Seattle do they have this?

it's only available in NY, US :/

reddit.com › r › dataanalysiscareers

Data Analysis Careers

June 11, 2024 - r/dataanalysiscareers: The place to discuss all things career-entry or career-related in the world of data. Do you have questions about how to get a…

Find elsewhere

Google Bing Mojeek

reddit.com › r/learnprogramming › 35 and want to start a career in data analytics

r/learnprogramming on Reddit: 35 and want to start a career in data analytics

May 13, 2023 -

I am 35 and I have a few months in between jobs. I recently did a certification in SQL with code academy. I’ve been told that SQL , Tableau and power BI has good demand in the industry. My background is in communications and I don’t have coding or Math background. Where should I begin and what certifications can I get? Also, is it realistic to start so late?

I’m turning 36 and I just started this year (Jan 2023). Doing my Computer Science Degree full time. Leaving my 15yr career in engineering design. So far I’m loving it. I’m married with 2 kids (15 & 10). Never too late to start.

Learn Python as well.

reddit.com › r/analytics › how's the job market for data analysts?

r/analytics on Reddit: How's the job market for data analysts?

February 13, 2024 -

Hi, I'm a math graduate and I've been looking into career options. I initially started with dev route but the dev market is just damn harsh at the moment and don't seem to be getting better any time soon, so I am looking into becoming a data analytics. I love problem solving, working with data and am just into all mathy things.

I have some transferable skills. I've done some academic research, where I used Python for dealing with data, and I know SQL from dev study I was on before. I'm thinking of picking up some more tools like Tableau, maybe R in the future.

I'm wondering how the entry-level job market is for data analysts. All my developer friends told me that the junior market for dev is doomed, everyone on internet told me the same so I feel that I need to steer off from this path. If it's similar for junior data analysts, I suppose I need to look for some other ways sadly.

Any advice will be greatly appreciated. Also if you have any skills in mind that I should learn for an analyst role, please share!! Thank you.

It’s tough out there, guy. Just got off the phone with a career counselor who really wanted to be sure I knew it wasn’t me- it’s industry. If you’re set on analytics, look towards retail, digital marketing, and the public sector.

Very competitive and saturated. Not far behind dev

reddit.com › r/leavingacademia › is something up with the data analyst/data scientist job market right now or is it just me?

r/LeavingAcademia on Reddit: Is something up with the data analyst/data scientist job market right now or is it just me?

December 15, 2024 -

Background: I have a PhD in social psychology that I completed in Spring of 2023. The last few years of my doctorate, I worked full time for ~2.5 years as an evaluation coordinator for a process evaluation of a statewide gun violence reduction program. After this (and most recently), I worked ~2 years full time in a supervisory role at a state office focused on criminal justice programs working with data, writing legislative reports, and doing some grant management.

Miscellaneous skills: I know R, SPSS, Power BI, and some SQL. I’m well-versed in multivariate stats, psychometrics, and even some Bayesian inference. I’m used to working with lots of forms of data, ranging from survey data to public datasets from the census bureau/FBI to SQL databases accessed through ODBC connections. I only have 4 peer-reviewed publications and only taught 2 classes during my PhD, but that’s largely because I pivoted towards acquiring non-academic work experience somewhat early in my program.

Problem: I’ve been aggressively applying to multiple positions for the past six months with very disheartening results. I’ve mostly focused on the public sector plus some non-profits and think tanks (I’m geographically close to the DMV, so the government-industrial complex is really THE big employer where I am). I’ve recently started applying to more private sector jobs too, though. Out of the dozens of positions I’ve applied to, I’ve only gotten one real interview. It’s rough…

Has anyone else in a similar position who left academia been experiencing this? Any advice to improve my search and/or prospects?

Oh, PhD in Physics here from a good US university. 10 years of experience, with python, c++, statistics, a bunch of papers, all about analyzing data. No jobs. A PhD won't get you automatically a job in DS.

The myth that there are plentyfull data jobs out there in industry for PhDs to pivot into was true 10 years ago but no longer. Yet it keeps being perpetuated in academic circles, because academia wants you to believe there are paved transition paths. 10 years ago, machine learning was new and companies went all in on hiring anyone they could as a data scientists, because they believed that they were sitting on untapped riches: their operational data. The frenzy gave rise to data science programs to cater to the demand and tons of PhDs who reskilled to get into the market. Then companies came to realize they can't do much with their expensive data scientists because their data is scattered, inconsistent, and low quality. Data scientists spend 90% of their time trying to get data and clean it up. Even when data science delivers a result, the impact is often disappointing in terms of ROI (see every churn model). Rarely do companies need fancy ML beyond a basic linear regression. Spagetti code from data scientists could not be reused. The focus shifted to building better technological foundations to support data operations. Roles in data engineering, platform engineering, ML engineering replaced a lot of data science. People with a software engineering background are better suited to these roles than academics or data science graduates. For the insights part, companies realized data analysts who run an ad-hoc SQL query on the data warehouse or work in Excel is enough. The data science hype died down, the market dried up, but the graduates and academics kept coming. For the data science positions that remained, companies could afford to be much more selective. Generally they prefer to hire those who worked in the industry; everyone else is considered a starter. Now the situation is even worse. There is a lot of economic uncertainty. For most companies, data is just a nice to have, not core business. Many are looking at their expensive data department as a source of savings. There are layoffs across the industry. So I can totally imagine you are struggling. The market for data science has been bad for years, and now the market for data roles overall is down too. Even with the technologies you say you know, companies look at your academic background and see a risk. Consider whether the following are an option for you: Expand your scope for roles & industries. Look for data analyst, data engineer, data manager, consultant, business analyst roles. Adjust based on whether you prefer technical work or working with stakeholders. Expand your geographic search radius Try to get a referal. This works best in smaller companies, and is so much more effective than applying through job boards. Do you know anyone who works where you would also consider working, and who could vouch for you and your skills? Reach out personally and ask whether they are hiring, and tell them about the value you bring to the table. This is how I got my first job as a data engineer after my post-doc. I came from applied physics. Best of luck!

reddit.com › r/datascience › whats your data analyst/scientist/engineer salary?

r/datascience on Reddit: Whats your Data Analyst/Scientist/Engineer Salary?

September 8, 2024 -

I'll start.

2020 (Data Analyst ish?)

$20Hr
Remote
Living at Home (Covid)

2021 (Data Analyst)

71K Salary
Remote
Living at Home (Covid)

2022 (Data Analyst)

86k Salary
Remote
Living at Home (Covid)

2023 (Data Scientist)

105K Salary
Hybrid
MCOL

2024 (Data Scientist)

105K Salary
Hybrid
MCOL

Education Bachelors in Computer Science from an Average College.
First job took about ~270 applications.

Data analyst remote 74k MS Poli Sci Laid off Delivery Driver 40k MS Poli Sci ... lol

2012: undergrad degree in math with philosophy minor 2012-2015: working in logistics & IT in Seattle, making maybe 50-70K. Learning everything I can. A couple certificates funded by work in Linux sysadmin, ruby development, and data science. I was also the TA for the data science certificate program the following year. 2015: masters in information systems while working part time. 2015-2021: researcher at AWS. Started in Seattle as a research scientist 1 @ 100k, ended as an applied scientist 3 in the Bay Area @ 450k. Learned a lot and made incredible money but burned out hard. Learned a lot about myself and what I value. 2022-present: principal data scientist at a pre-IPO startup @ 250K (still in the Bay Area but working remotely). Work life balance is good, I really enjoy the problem space and the people I work with. It’s a strange feeling realizing that I’m now solidly mid-career, but I’m grateful for how things have turned out.

reddit.com › r/dataanalyst › data analyst in 2024 - no way at all

r/dataanalyst on Reddit: Data Analyst in 2024 - no way at all

February 5, 2024 -

I do see many, many who want to work as a Data Analyst in 2024 and I absolutely wonder why....

If you look for the Search keyword "Data Analyst," this is one of the hardest keyword difficulty in the world, meaning there are literally hundreds of thousands of websites ranking for this job/keyword
The next 5-10 most searched keywords in Google are coming from 3rd world countries and are tagged with "Data Analysts Jobs" "Data Analyst Career" etc. etc.
In Google Trend the search trend for Data Analyst goes up BUT only as well only from so-called 3rd world countries and all related to jobs, carrer, studying, certificate

In sum, the market is totally oversaturated.

I think the simple answer is that we have an increasing amount of data, something about that data is doubling every few years. The job of a data analyst is to turn data into an insight.

I think the key to a career in data is having a personality, leadership skills and superior communication skills. I’m having a great time because EVERYONE in this department is an introverted nerd that can’t seem to have social interactions. Meanwhile I led a sales team for 15 years before transitioning to data analysis because I found it interesting. Analyzing data/business is one thing. Communicating that to executives is a whole other ballgame.

reddit.com › r/datascience › what is the current job market in data science? (june 2023)

r/datascience on Reddit: What is the current job market in data science? (June 2023)

June 20, 2023 -

Title

Not great. OK if you're experienced (>= 5 years). If you're entry-level, it's terrible.

Pretty bad if your idea of "good data" is getting opinions on reddit rather than using actual job/hiring data.

reddit.com › r/dataanalysiscareers › is learning data analytics in 2026 still worth it for freshers?

r/dataanalysiscareers on Reddit: Is learning Data Analytics in 2026 still worth it for freshers?

January 9, 2026 -

Hi everyone, I’m a fresher and currently planning my learning path for 2026. I’m looking for honest and practical advice from people who are already in the data field.

First of all, is Data Analytics still worth learning in 2026? I’ve heard very mixed opinions. Some people say the future is very bright, while others say there are almost no jobs for freshers.

I’ve also heard that many people complete full Data Analytics courses but still struggle to find a job for 3–4 months or even longer. So I want to understand — are jobs really that limited for freshers, or are these just exaggerated / fake claims?

If Data Analytics is still a good option, I would really appreciate guidance on a clear learning roadmap, for example: • Where should I learn Excel from? • Where should I learn SQL from? • Should I learn Python (and to what level)? • What about Power BI / Tableau? • In what order should a beginner learn these skills?

Also: • Are certifications like Google Data Analytics, IBM, Microsoft, etc. actually helpful for getting interviews? • Is self-learning + projects enough, or is a paid course necessary?

And if there is anyone here who is currently working as a Data Analyst, please share your personal experience: • How did you start? • How long did it take you to get your first job? • What skills mattered the most? • What mistakes should freshers avoid?

Thanks a lot in advance 🙏 Any genuine advice will be really helpful.

USA. graduated in 2023. worked remotely as a data analyst for 1.5 years with a promotion until a layoff. now i've been unable to get an interview, it's been a year.

The DA skills are very helpful for all kinds of positions that aren't DA. In the US at least, if you don't have at least five years of DA experience already, then it is an extremely tough job market. PL-300, the Microsoft certification for Power BI, is the only one that I've seen be considered of much value in DA and that is in some IT shops that are Microsoft shops. Most of the "certifications" or certificates do not really have the testing thoroughness that is useful for employers to give any weight to. The priority order is in most cases Excel->SQL->Power BI.

reddit.com › r/dataanalysis › what’s pros and cons being a data analyst?

r/dataanalysis on Reddit: What’s pros and cons being a data analyst?

October 16, 2023 -

So I’m interested in taking a course to get a cert in being a data analyst maybe even in cyber security. I’m just wondering from primarily experienced people in this fields what’s the good and bad starting out? I’ve been doing research already and seems to be a lot more to this field. Like business intelligence, data engineer etc, I’m a veteran just weighing my options. I may even go school and get a degree in this field if I decide I really like it. Also, been hearing good government jobs hire and good pay for this kind of remote work…

https://mavenanalytics.io/find-your-path This is a useful resource for beginners to best determine which area within data their interest lies. With you being a veteran, I would suggest connecting with a LinkedIn content creator, Albert Bellamy (veteran turned Alteryx instructor). He’s very generous with his time and will certainly answer any questions you may have.

Professional sr. data analyst going on 9 years. It’s a fine career … as long as you’re personally committed to constantly building your skill set and finding the best ways to apply your constantly evolving skills. Several organizations I’ve worked and/or freelanced for are obsessed with the new hotness all the time. No certificate/bootcamp/etc course is going to make you worth a whole lot, but they can help you learn something to get a foot in the door. My biggest career successes have come from me realizing a different tool is needed to optimize things, given the constraints… and you have to learn just enough of a shiny new framework to get the job done. This is a crazy space to be in because literally everybody is trying to chase the new hotness every damn day. And… you’ll find that at least 70% of your job simply comes down to keeping stakeholders grounded in their requests. Soft skills are more important than “hard” data/query/programming skills here because you quickly realize people don’t know how to ask the questions they really want to ask and you have to constantly refine THEIR questions… for weeks, sometimes, in order to ensure you can get them what they want. They have questions, but they rarely actually know what they want, if that makes sense. Working through this is a huge chunk of the job. Writing queries and designing visuals for summarization is fairly easy once that hard part is done well.

reddit.com › r/businessintelligence › is it worth studying and getting a job as a data analyst today or is it a sector which will get replaced by ai soon?

r/BusinessIntelligence on Reddit: Is it worth studying and getting a job as a data analyst today or is it a sector which will get replaced by AI soon?

May 16, 2023 -

Just would like to hear your opinion on this one. I am currently trying to change career switching in data analysis.

there are several reasons why this is not going to happen soon: Users need to provide clear requirements (definitely not going to happen) Transactional and master data degrades in time, no matter how well thought and curated your initial process/data is. End users are "creative" in the worst possible way, no business process is 100% used as intended. Business processes usually have non-written rules, no AI can "model" this yet based on loose criteria, and key users usually hide/obfuscate these criteria to keep their jobs Strategic goals usually are not aligned with current business processes or impaired by poor data quality, change management across the organization is required to implement solutions successfully. So basically you need perfectly curated data, and a business process used as intended and aligned with strategic goals since the beginning of time so AI can completely replace a business analyst. On the other hand, AI will support analysts on a daily basis on these boring but necessary tasks.

AI is nothing to be afraid of. It's not going to replace data jobs, if anything it's going to make the work we do 10x cooler.

reddit.com › r/dataanalysiscareers › making career as a data analyst in 2025

r/dataanalysiscareers on Reddit: Making career as a data analyst in 2025

June 3, 2025 -

I have worked as a virtual customer service for 3 years and now trying to learn data analytics and i have tried learning it previously as well but I didn’t give it time. Now i have time as i left my job so will you help me with some tips and ideas how to get started and keep up to date with learning. I watch videos and understand the concept but while try to solve the problem i have to go back to watch video so is it okay in starting?

You can learn analytics that way, but your real challenge will be that most jobs aren't hiring someone without a formal education or previous experience.

Skills matter and with right project you can achieve that dm for guidance

reddit.com › r/analytics › the future of data analysts

r/analytics on Reddit: The Future of Data Analysts

October 7, 2025 -

From following this thread in recent times, I have noticed people mention struggling to find roles as a data analyst. As I approach graduating with an information systems degree, I am wondering if this is due to one of the two following reasons:

First, more plainly, the job market itself is down, and less opportunities are out there. Second, my theory is that many of the data analyst responsibilities have been absorbed into other positions within company. This may be due to advances in technology (dashboards, AI, etc) or also in part to companies slimming down and consolidating responsibilities. I am curious if this may be the future of data analytics.

If anyone has any opinion about this, please share. If I am completely wrong, let me know. This is just sort of the impression I’ve been under. Data analyst is a career I’ve been interested in for the past couple years, but if it’s now harder to find a position, then I may try to pivot into something else.

Domain over data. Anyone can piece together a star schema. Not everyone can create actionable insights that drive the business towards success.

The industry is shifting. There are plenty of jobs, but folks often want the full remote and 80k to start. It's not going to happen. My first role as an Operations Analyst was $45k a year. I went into the office every day and wore a suit since I worked for a bank. I was just happy to get a job that I could develop some skills. Now, the other side is just knowing SQL or making cute little dashboards isn't cutting anymore. People need to know how to communicate and how to translate findings into action, and you must know how to data model. The industry is hyper focused on Data/Analytics Engineers because the world of AI needs lots and lots of clean data. And, with every DB giving us access to wonderful Data Science functions, it's never been easier to use LLMs or create ML pipelines all through SQL. So the future is being full stack, and being exceptionally good at communicating. Anaylsts are a client facing role, meaning you must be a strategic partner to stakeholders.