r/DataScienceJobs

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I’ve been noticing this a lot recently.

Many people already know Python, SQL, Excel, Power BI, Machine Learning, Deep Learning, or even MLOps. They’ve completed courses, built projects, and spent months preparing.

But even after applying consistently, they still face:

rejections,

ghosting,

endless assignment rounds,

or “we moved with another candidate.”

After a point, it becomes mentally exhausting.

I honestly think the issue for many learners is not a lack of effort. Most people are stuck somewhere between “learning concepts” and “being industry-ready.”

Things like:

choosing better projects,

explaining projects clearly,

interview communication,

practical problem solving,

and understanding what companies actually expect from freshers

seem to matter much more than just completing another course.

I’ve personally been spending time practicing projects, interview prep, and discussing these things with other learners online, and it made me realize a lot of people are going through the exact same struggle quietly.

Curious to know from others here:

What has been the hardest part of your job search journey so far?

Greetings

I have been invited to an interview after applying at IBM. I previously experienced each application demanding an online assessment, but this time round it appears it was not necessary.

After recieving contact from recruitment for additional information to support the application-

I have been invited to be interviewed here in the UK to have an in-person interview. Which is somewhat off-putting as its usually virtual from my experiences with consulting groups. (I live far from the on-site interview locations which will be costly in time and money). Would it be fair to ask if they could potentially accomodate a virtual interview?

I've been informed that for this role, it is a "single 90 minute on-site panel interview with two practioners from the business covering both technical and behavioural".

Approaching this role with only 3 years in experience consulting within ML/DS/DE domain with the goal to do more MLOps.

Any ideas on what to expect/ what we will cover? Live coding etc etc.

It's been a week since my interview. I haven't heard anything yet. Given that it shall start soon, has anyone received final results? If you applied last time, how much time did it take for results?

Hi everyone,
Posting for a friend who just hit some brutal luck. He recently finished his Master’s in Data Science and interned at a US startup for 10 months. They were supposed to transition him to a full-time role, but backed out at the last second due to budget/hiring freezes.

He loves the startup grind and is looking for a Data Science or Software roles in US.

If your company is genuinely hiring or you have a referral, **please DM me and I will send his resume over immediately.** Thank you!

Hey everyone,

With all the AI-driven layoffs happening (Meta cutting 14,000 positions), I'm trying to be smart about what I learn next.

My current profile:

- Python, Pandas, NumPy, Scikit-learn, SQL, Streamlit, Git

- Projects: California House Price Prediction (deployed on Streamlit), Netflix EDA (Kaggle Bronze Medal)

- Day 50 of CampusX 100 Days of ML

- Starting a 3-month internship at an AI startup

What specific skills, tools, or areas should I prioritize RIGHT NOW to stay relevant and land a good Data Scientist or ML Engineer job/internship?

Any honest advice is appreciated. Thanks!

I'm about to start a Data science internship this month. Last Monday someone from HR shared my mentor and manager's name with me and their emails and said I should reach out if I have any questions. I just reached out to my manager today asking if there's anything I can review or do before starting. He gave me some things to review and then also said my mentor will be introducing herself this Friday too and to look out for that.

Should I introduce myself to my mentor before she does? I was thinking about emailing her but I just don't have any questions or anything? I feel like I've done something wrong especially the fact that he told me it almost felt like I was supposed to email first. For context, this is also my very first internship 😭

With the growing demand for tech skills worldwide, where do you think the best opportunities exist for professionals in Data Analysis, Data Science, and Artificial Intelligence — both in the job market and freelance industry?

Which field currently offers:

More job openings?

Better freelance opportunities?

Higher income potential?

Easier entry for beginners?

I’d love to hear your thoughts and experiences from different industries and countries.

Hi everyone so I am woman getting a master degree in Data Science. I don’t want to directly work with data science but I plan to work as data analyst something related to this. The thing is I am really bad in math so I am struggling with the course. Of course there’s some self sabotage as I know that I need to study more, than I study the bare minimum and blank out in the days of assignments.

I really think it’s fascinating the statistic part and coding part, but I have always been the “humanities” person but seriously I don’t like to work with this! I even tried to work with content creation and I hated it. But I was really into the ananlytics/ADS part. Is that even possible?

Main question: can I be VERY good professional as data analyst being not a math person?

Thank you

What would be a preferred course to take between data science and Ai, data analysis and data engineering. Which one is more marketable and has for job opportunities both in freelance and job space

Hello all,

TL:DR I landed ass backwards in this field and I'm not sure what the 'next steps' are. I've got some time coming up, and I want to know what are some good tools to learn if I choose to advance in this field.

____

After losing my corporate job (legal firm) last year I couldn't find anything other than Uber for 8 months. I landed this job at a school by ACCIDENT, basically lied through the interview. But I was self sufficient within a month, and my Boss said I'm the greatest hire he's ever made. So that's encouraging.

My title is 'Data Manager', but some Googling makes it seem like I'm a Junior Data Analyst, Operations Analyst, or Reporting Analyst. I'm basically creating automated reports and answering ad-hoc queries for different departments.

I'm pretty advanced in Excel (functions, V-lookup, pivot tables, etc.), and I know the basics of SQL, and I've got a pretty good grasp on my School's schema structure.

I know the basics of Python, I've never touched R, but I'm happy to learn, but I didn't know if tools like Tableau or Power BI would be better to start with.

Bit of a weird post, but here goes.

I’m a Machine Learning / AI engineer with experience building and shipping production AI systems end to end. I’ve worked on LLM pipelines, RAG systems, FastAPI microservices, vector databases, AWS SageMaker deployments, backend systems, and production ML infrastructure. Worked at startups and fast-moving teams where ambiguity was normal and you just figured things out. Also worked on a government-funded cancer recurrence research project and have experience across BERT, XGBoost, OpenAI, Gemini, and production deployment workflows.

Reason I’m posting. I recently joined a new role on a contract basis and honestly, I’m realizing pretty quickly it’s not the right fit. The environment feels rough. Founders publicly scolding people during scrum calls, everyone overloaded, very little bandwidth to onboard or help, and that weird feeling where people protect work because they’re already drowning in dependencies. I get startups are chaotic. I actually enjoy chaos. But there’s a difference between moving fast and burning people out.

So if anyone knows teams hiring for ML Engineer, AI Engineer, Applied AI, GenAI, or backend-heavy AI roles, remote or Bangalore preferred, I’d genuinely appreciate a referral or even pointing me in the right direction.

Happy to share resume, GitHub, LinkedIn, whatever helps.

Hey, my cousin graduated last year with an M.Sc. in Data Science and an 8.4 CGPA. She has basic working knowledge of SQL, Power BI, Tableau, and Excel. She’s extremely hardworking and intelligent, but she’s really struggling to land an entry-level job.

We’re based in North India (Chandigarh region), and there don’t seem to be many good opportunities here. One major limitation is that she can’t relocate to another city right now and is specifically looking for remote/WFH opportunities or in the hometown area.

Where should she begin? What additional skills would actually improve her chances? What’s the right way to apply for entry-level roles in this field? Also, are there any good companies that offer paid or even unpaid remote internships for freshers in data science or analytics?

I’m trying to understand the real learning process behind coding in Data Science, especially when working with datasets on platforms like Kaggle.

Right now, it feels like most of the time I’m just searching things like:

“How to extract specific columns in pandas”

“Which function to use for grouping data”

“How to clean missing values”

And while I understand that Googling is part of programming, I’m confused about where the actual learning happens in this process.

For example: If I’m working on a dataset and constantly looking up functions and methods, how do I eventually develop the ability to write code independently without relying on search engines every few minutes?

Is the learning supposed to come from:

Repeating Kaggle notebooks?

Studying libraries like pandas/numpy deeply first?

Doing structured courses before touching real datasets?

Or is it normal in the beginning to always rely on Google and slowly things “stick” over time?

I feel like I understand concepts in theory, but when I open a dataset, I struggle to translate that into actual code.

I'm working at a project in Micro1 and in the last days, the hiring manager asked for referrals to the open positions. You can check it here the openings.

I'm working atm in a project that is paying me $65/h to analyze quality of publications in Data Science.

The pay changes based on you location and experience.

You should send you CV and make the AI Interview. If you have a good good interview results, you can send me a message to the hiring managers :)

Also, if you want to see how the interview works, they offer an Mock Interview so you can understand and prepare yourself (i also did it several times so i can help you by sending the questions that appeared the most)

Check the Mock Interview Here : https://www.micro1.ai/interview-prep?0_name_contain=Data+Scientist

and good luck :)

I am joining OMD in chicago this summer as a data science intern. I am really excited and eager to learn in this internship, but I do not know what to expect. Are there any tips? How is the work life? Is there anyone else joining this summer? I would love to connect!

let me know if you have feedback! https://pagesxyz.com/data-science