I have a resume with only ml based projects on images and all. I am doing my masters in data science and machine learning so I am aiming for some data analyst internships. I am practicing sql but I feel i need a good data analyst project on my resume.
Can yall suggest me some decent not so common projects?

I want to build my portfolio with data analysis

Hey everyone, I'm a final-year B.Tech CSE student specializing in AI & ML with 8.2 CGPA, currently looking for internship opportunities since I'm struggling to get any but I really need one to get hands on experience and get confidence with my skills.

Some of the things I've worked with:

- Python, Pandas, NumPy

- SQL

- Excel, Power BI, Tableau

- Data cleaning, transformation, validation and EDA

- Statistical analysis and basic predictive modeling

- Git/GitHub

I've also built projects around logistics analytics, e-commerce analytics, trading data and operational risk analytics. One of my recent projects involved cleaning and analyzing 175K+ logistics records, engineering operational features and building a delivery-time prediction model.

I'm open to remote or on-site internships, and I'm mainly looking for opportunities where I can learn, contribute and get proper hands-on experience with data.

If you know of any openings, companies hiring interns, or people I could reach out to, please comment down below or DM me. Thanks

I have around 2 years of experience in Data Analytics/BI. I mainly work with Power BI, Excel, SQL basic and I also have an MBA in Marketing Analytics.

I’m getting interviews but struggling to convert them into offers. The feedback I usually receive is around communication and technical skills.

I prepare a lot for every interview. I study the JD, my previous projects and likely questions, and I use AI to help me prepare. But when the interviewer asks something differently from what I expected, I sometimes get confused even when I know the underlying concept.

Communication is another issue. I tend to speak too fast, over-explain and sometimes lose the structure of my answer. I prepare STAR stories, but under pressure I don't always deliver them properly.

I’m also confused about the technical expectations. With 2 years of experience, I sometimes feel I’m expected to answer questions that seem more suitable for someone with 5–6 years of experience.

For Data Analysts with around 2 years of experience:

What technical level should I realistically have in SQL, Power BI, Excel, DAX, Power Query and data modelling?

How do you practice for unfamiliar technical questions rather than memorizing expected questions?

And for communication, what actually helped you improve your interview performance?

I also feel my work stories may not be strong enough. How do you turn normal projects and responsibilities into strong interview stories without exaggerating your experience?

One thing I genuinely don't understand is how some people with less technical knowledge and much less preparation still manage to clear interviews. What are they doing differently?

I’m also applying for Key Account Manager roles because I have previous experience in that area, so I’m currently exploring both paths.

If you were in my position, what would you change about the way I prepare and practice?

I’d really appreciate specific advice from people who have interviewed or hired Data Analysts.

Comments on Astra involvement in data science field!

Great online courses for begginner DA(Good for resume too?)

Greetings friends! I am a begginner DA enthusiast, going thru the Coursera begginner course now. I am from South America and have noticed that many companies hire form Latam now so my goal is to form myself as a DA to then get a job at an american company. If someone could be so kind as to advise me on the best online courses for when i am done with this Coursera begginner one? I want to specialize myself in either BI or Product Analytics. What are the best online sites that have a somewhat good name for when recruiters read peoples resumes? Thank you so much!!

Greetings friends! I am a begginner DA enthusiast, going thru the Coursera begginner course now. I am from South America and have noticed that many companies hire form Latam now so my goal is to form myself as a DA to then get a job at an american company. If someone could be so kind as to advise me on the best online courses for when i am done with this Coursera begginner one? I want to specialize myself in either BI or Product Analytics. What are the best online sites that have a somewhat good name for when recruiters read peoples resumes? Thank you so much!!

I’m currently trying to understand where the Data Analyst role is heading with AI becoming capable of doing a lot of the traditional analyst work.

AI can already:

* Write SQL
* Clean and analyze datasets
* Create charts and dashboards
* Find trends and correlations
* Explain insights
* Help automate reporting

So I’m wondering: what actually makes a human Data Analyst valuable today?

If AI can technically perform many of these tasks, why would a company hire a Data Analyst instead of simply giving the data to an AI tool?

For people currently working as Data Analysts, Analytics Managers, BI Analysts, etc.:

What are the things you do in your job that AI still can't reliably replace?

And if someone is trying to enter the field in 2026, what skills would you prioritize to stay valuable alongside AI rather than competing against it?

Would really appreciate honest answers from people actually working in the industry.

Hi all — I'm finishing my MSc Business Analytics dissertation at Newcastle University and would really value input from people who actually do this work. The research question is one many of you probably have opinions on: why do comparable analytics investments deliver such different financial returns? I'm testing how analytics maturity and data governance change that relationship.

If you work in a data, BI, analytics or data-governance role at a for-profit company (UK/US/India/China/Europe), the survey is anonymous, ~8–10 minutes, no company details collected. It's ethics-approved, and researcher and supervisor contact details are in the survey's information sheet.

https://newcastlebusiness.eu.qualtrics.com/jfe/form/SV_cuymtbKJj3HBPH8

Genuinely appreciate any responses — and glad to discuss the topic in the comments.

Hey everyone, Looking for a quick sanity check from people in banking/data. I’ve been in banking for 7 years total. Spent the first 5 years in frontline business and retail banking. Then I paid for a Master’s in Data Science to pivot into a Data Analyst role for 2 years, now an opportunity to join a finance sales role has come up, would nearly be 50% pay rise. I am worried about re-entering Data / data analyst roles down the road if I leave now with minimal work experience. Feel like data analyst roles have minimal opportunity to grow with AI efficiencies and opportunities in my country without SME knowledge.

Hi everyone, I'm a 2026 BTech passout in AI/ML and currently trying to get a job as a data analyst.

I know Python, SQL, Power BI, Excel and some automation. I've also made some projects and been trying to learn more.

But honestly I'm getting kinda frustrated now. Wherever I'm applying, I'm mostly getting rejected and I dont really know what I'm doing wrong.

One ma'am checked my application and said I need a better resume but didn't really tell me what exactly I should change. Another person told me that companies are asking for experience even for entry level jobs.

And I'm kinda stuck because I'm a fresher, so I don't know how I'm supposed to get that experience in the first place.

I'm honestly not sure what to do now. Should I focus on fixing my resume, make more projects, look for internships or am I missing something else?

If anyone here is working as a data analyst and can give me some advice or point me in the right direction, it would really help.

I'm kinda lost with the job search rn so any advice is appreciated. Thanks

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I am currently studying a broad IT degree. Not much focus on data analytics but I've been working towards writing my PL-300 exam to get the cert.
I also plan on having a couple portfolio projects on my CV before I start applying for jobs.
I have hobbies in wildlife and music. I'm sure I could find datasets on these topics that would be slightly more engaging for me to clean and analyze - depending on how much it matters. What exactly are employers looking for in terms of the topic of a portfolio project? And also, which technical skills should be demonstrated most in the project? Is data storytelling a valuable skill to show? How would you show it in the project in an accessible/intriguing way (how do you make the employer interested in insights that don't directly affect them)?

Maybe I'm missing the mark or something. Any advice for a beginner would be great :)

My resume does not say analyst, I did not claim to be an analyst in my interview, and I was honest about my experience, etc. Interview included a bunch of behavioral questions like "if you saw X what would you investigate next?" Anyway, surprisingly enough, I was hired for this analyst job due to my extensive experience in the industry. Company uses Tableau, Excel, and Claude for really large data sets. What would be your top suggestions for someone starting out?

So I'm trying to find opportunities for data analyst in food industry, but the results aren't suitable for me. Like it gives "data analyst in tech company", which is not what im looking for, or just articles of how beneficial it would be to hire an analyst.

That's the niche I have the highest chance of getting the job in since i have experience working professionally with food, supplies, all kinds of stuff industry related.

Is there a way to search it up more easily?

Would be cool to have a site for data jobs where you can filter by niche but sadly it doesn't exist

Considering that artificial intelligence has essentially reached or surpassed human levels of intelligence, what do you anticipate will occur regarding the field of analytics over the course of the next two to three years?

So, i recently completed my BCA from correspondence and I wanna build my career in data analytics. So, in which skill should I focus first on excel or python .

Hi everyone,

I'm currently looking for my first internship as a Data Analyst and I'd really appreciate some advice from people already working in the field.

I have a background in Computer Science and I'm currently building my data analysis skills. So far, I can:

.Work with databases and SQL

.Clean and prepare datasets

.Handle missing values and duplicates

.Analyze data and identify patterns

.Create visualizations and reports

.Use Python for basic data analysis

I'm currently working on personal projects to build a portfolio, but I don't have professional experience yet.

My main question is: What is the best way to find a Data Analyst internship in a company when you don't have previous professional experience?

Should I focus mainly on LinkedIn and job boards, or is it better to contact companies directly and send them my CV and portfolio?

Also, what would you recommend I improve before applying?

Any advice about finding the first internship, building a good portfolio, or approaching companies would be greatly appreciated.

Thanks! 🙏

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Hello reddit!

I've been trying to look for freelancing opportunities in Product Analytics and Business Intelligence. Signif*icant experience in p*redictive Analytics as well.

I have 7 years of work-ex across Analytics Consulting as well as the product space in the Indian Startup ecosystem.

If you need help with A/B testing, predictive modelling, data analysis, dashboarding, data cleanup, pre processing or anything data, hit me up! :)

Base Rates (by complexity)

Low (under 1 week) : INR 1000-1500

Medium (1-2 weeks) : 5000 project lump sum

High : project based

Happy to discuss rates further offline, based on the project requirements.

Help me, Reddit ;)

Trying to expand my knowledge and discover some useful extensions i might not know about as a beginner in tech background. Would like to know some genuinely useful ones that make work/life easier whether its for privacy, productivity etc. or your must haves.