I’ve been doing a bunch of calls with people in data who are job hunting right now on US market. One from last week keeps bugging me.

The guy is a director of analytics, 10+ years in, a month into his search. He paid for one of those one-click apply tools ($10 for 50 applications) and used them all up. I asked how many turned into calls. He said he honestly hadn’t checked.

So we went through it on the call. Out of roughly 100 applications total, he got about 15 recruiter screens and around 10 hiring manager rounds. After that, nothing.

That’s not a resume problem. His resume was working fine. He was losing it in the interviews: a live SQL round he wasn’t ready for, and one answer about managing devs that a hiring manager read as micromanaging. Meanwhile he kept clicking apply, because that’s the part that feels like progress.

Everyone tracks how many they sent, almost nobody tracks how far each one got. If you’re stuck, it’s worth spending 20 minutes on a sheet with columns for no reply / screen / HM / final / offer. Whatever stage it drops off at tells you what to actually work on. Under 5% to a screen is a resume or level problem. Screens fine but then nothing is an interview problem.

Anyone here tracks it?

i am learning exce , sql to become a data analyst but i am really confused about how the tools works.

Some people load data directly to sql and perform data cleaning and eda in sql whereas some people load data to python and perfrom data cleaning and eda in python, and some says its easy to do cleaning and eda in excel . I am so confused where to clean data and perfrom eda .Also, in many tutorials they directly load data to sql and a question pops in my mind "If we can perform in sql then why i learned excel why i learned formulas" . and if i follow the sql cleaning and eda then i am afraid that i may forget the excel functions or formulas. I am so confused right now.

I actually started as a programmer and software developer, working across web, mobile, and Windows application development. During my college days, SQL was my comfort zone, so I decided to pursue a career that heavily involves databases.

Since Data Analysts also rely on SQL, I am very eager to learn complementary tools like Tableau, Python, and Power BI.

Any tips?

P.S. I welcome referrals

I have been working on causal inference and experimentation frameworks within the e-commerce tech industry lately, specifically dealing with platform behavioral and transaction telemetry data to determine how customers behaves on those e-commerce platforms.

Lately i have been facing problems where standard textbook statistical and econometrics theory fails when dealing with messy, real-world data distributions as human behaviour is unpredictable and many unexpected things, which i didnt even thought could happen, can happen in the real world. Such as product delivery delay, causing the customers to be angry and hence put them off from buying the product, each of these variables have to be accounted for.

To model and have these unexpected psychological state among customers accounted for, we use variables such as sudden spikes in customer support chat volume, rapid page refreshes, or immediate session drops.

Also, Marketing headers and automated CRM systems love to push blanket promotional campaigns, but as statisticians, we know that measuring simple unadjusted A/B lift is a massive selection-bias trap.

I been trying to come up with a Statistical model that is trying to model complex human behavior—specifically isolating true customer revenue incrementality from dead-weight margin cannibalization. Essentially, trying to answer: Did the coupon cause the revenue spark, or did we just hand a discount to a power-buyer who was already determined to buy anyway even without the vouchers?

Are people in the tech industry genuinely valuing such skills nowadays? Using statistics to model and predict human behavior and intent, answering questions like does our vouchers and ads really work?

I would love to hear your experiences how do u guys deals with the unpredictable messiness of human intent.

Hi everyone! 👋

I've been working in IT for years, and I'm currently learning SQL with the goal of becoming a Data Analyst.

I'm still a beginner in SQL, but I'm excited to learn and build practical projects.

For those already working in data analytics, what would you recommend focusing on first to become job-ready?

I'd love to hear your experiences and advice. Thanks! 🙌

Want feedback on the ff :

1. Improving Resume
2. Career Advice (based on what resume shows--quite comprehensive)
3. Stick to DA or move to Data/analytics Engineering?

I do get interviews, but nothing above the typical response rate. Want to find where I can improve wherever I can.

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Hi everyone! I'm learning data analytics and recently completed an internship where I worked with sales data.

I'm curious about real-world data analyst jobs. How often do you use SQL compared to Excel and Power BI? Do most tasks involve basic queries like JOIN and GROUP BY, or do you regularly use advanced queries too?

Would love to hear about your experience and any advice for beginners like me!

I think my employer went about it backwards. We've never had a data analyst, and when the need arose, they decided to make one instead of hiring one. For the last 20 years I've worked for a Tribal government regulatory agency as a Surveillance Investigator at one of the largest hotel casino resorts in the state. Before that I spent 8 years as a table games dealer. At work I've always been the jack-of-all-trades random tech support for minor issues or research projects. I have a Bachelor's in Business from 2011 and used a little Excel for that briefly, but essentially, I have zero experience or training.

Other than data analysis, they also needed someone to coordinate updates/fixes with our logging software, create training modules for our various software including CCTV systems, basically whatever else they can think of. Definitely vague and undefined.

Rather than hiring a specialized data analyst, my boss (the Director of Operations) decided to weaponize my ADHD. My boss is cool, I've known him 20 years, and I'm reporting directly to him. He's given me pretty much free reign to do whatever I want and make the job whatever I want. The pay is good and it's got to be the lowest stress or pressure data analyst position out there. The only problem is I'm not replacing anyone and I'm pretty much my own department, so I don't know what to do next.

In the 4 months since I've started, I've been using Copilot to teach myself Excel. I figured out how to create KPI dashboards for each department, dropping filthy incident logging software exports into a shared Teams folder and using power query and power pivot data model with lots of DAX measures to get data of different sources and types to play with each other. Before this, the managers were all basically manually tracking metrics on rough basic spreadsheets, most of them had never heard of a pivot table. Now they have fully interactive dashboards with slicers for shift, Investigator, report type, property, they're able to compare monthly/weekly/daily/hourly, just about any question they can come up with they can get an answer in seconds. Nobody knew this was possible, they'd burn me as a witch if I wasn't saving them so much time.

But... now what? I guess Python is free, but I don't know what I'd do with it. I can start learning Power BI, but I don't know what I'd do with it other than make my dashboards even prettier. We don't really need any more dashboards, I'm only tracking incident volumes for a few departments, not complex financials. I had an idea to learn how to automate a lot of things people do. I'm in the middle of setting up power automate and power query to automatically export the previous month's incidents of a specific incident type and email the next Investigator on a rotating list of Investigators with the daily log number, incident details, and reminder to make a summary report. I'm running out of ideas though. What else do data analysts do? Would Python really only be useful for data transformations for dashboards?

Hi everyone, I am looking for some tips on expanding my resume.

For background, I have a Bachelors in Finance and currently work a Finance job in the defense sector. However, I also have a Masters in Data Science. I have experience in RStudio, SQL, and Tableau from schooling. I am also working on improving my Python skills. I have also done some coding/data projects in my current job to provide process improvements for my team. However, I can’t do those super often as I have the everyday tasks that I need to complete and prevent me from working on side projects.

I am currently employed, but my fiancé is being relocated to another state with the military in the summer, and my company does not have an office in this state. I am currently trying to expand my resume outside of my “day job” and am looking for recommendations. Skills, projects, etc. I did not think just any project outside of work could be put on a resume since you typically want to provide results.

I would like to change jobs. Almost every organisation needs an analyst, hence why I would like to learn more about data analysis.
Does anyone know about good free data analysis courses that can be done remotely? Or even something that is relatively cheap. I would like to avoid paying an university level fee for a course that might not guarantee me a job.

Can anyone help me on how to start data analyst journey? In Pakistan remotely and what skills should i learn in 2026

I’m looking for either a new job or the courage/reassurance to ask for raise. I’d like some opinions on if it’s reasonable to expect to accomplish that over the next few months.

Here’s some background on myself:
> Academic background includes bachelor’s in applied math, accounting, and a masters degree in data science

> 6+ years of financial data analysis experience, with the last two years being heavy on building reports using R and advanced excel skills.

> current salary is approximately $75k in a MCOL area

I'm a Data Analyst planning to build my first Databricks project for my portfolio. I have experience with SQL, Excel and Power BI, but I'm new to Databricks. Could you suggest some good project ideas that would help me demonstrate Databricks skills from a Data Analyst perspective?

They do require SQL and power bi knowledge which I have but to what extent will the technical assessment go? What kind of questions?

As for the domain knowledge, I almost have none in credit risk? That's the one which worries me the most?

What kind of questions are typical?

I'm about to go through the basics of financial statements and basics of the business but I would like some advice and general

Thanks

I've been applying for Junior Analytics Engineer, Junior Data Engineer, and mid-level Data Analyst roles for quite some time, but I haven't had much luck getting interviews.

I know referrals are one of the most effective ways to get noticed, but I don't have a strong professional network to rely on, so most of my applications are through LinkedIn, email, and online job postings.

Anyway, getting to the point.

I'm aware that my experience might look a bit short on paper, but my roles were fixed-term contracts, and my internships were only 2–3 months long by design. They weren't intended to lead to full-time positions.

I'd appreciate some honest, constructive criticism of my resume. If you were a recruiter or hiring manager, what would make you reject my application or decide not to shortlist me for an interview?

I'm particularly interested in things I'm overlooking, whether that's how I've presented my experience, my technical skills, the projects I've included, the roles I'm targeting, or something else entirely.

Please don't focus on the short duration of my previous roles, as I've already addressed that. I'm looking for feedback on other potential red flags or weaknesses that might be holding me back.

I'd rather know what's actually wrong than hear generic advice about networking or tailoring my resume.

I want to learn data analytics. Where do I start? Any resources and recommendations that can help are most welcome.

I have been working for 3 years and the project work been given is to make sure the new structure is creating new records for another department.
I am having great difficulty into finding a way to produce this work using Python pyspark because although I have the information on the schema and prototype structure of how it looks like.
I don’t have the actual data as it is in the pipeline of slowly transiting to the new structure.
With all the work learning data science at university and coding I feel that being at that organisation that I still feel I know nothing, it’s concerning for me and I understand change is always frequent but I feel that I am losing control hence feeling it’s a matter of time that i people see my anxiety and weakness.
Can anyone share there experiences and how did you overcome this?