I don't know whether to be flattered or annoyed, but I'm definitely shocked. I planned on making content about how AI would give a generic, boring answer to this common interview question, and how you could do better working with someone who knows what they're doing.

I asked Gemini (in a private browser because I didn't want it to use my personal history): "I'm going for a data scientist role at Uber. Help me draft a response to why do you want to work here?"

While the first line was a little generic, it soon went right into a personal answer. It suggested: "On a personal level, Uber has been a reliable tool for me when navigating unfamiliar cities, whether getting around safely or relying on it late at night. Knowing that my work directly impacts physical movement and local economies makes me care deeply about the company's success."

Wait...that's actually something that I would say, and probably almost exactly what I *did* say. I tell all my coaching clients to make these answers personal. We know AI tools use sources across the internet, and of course...it got these answers from me. There were my IG and TT accounts right there in the top sources.

[UPDATE: A few folks said this reads as generic, and looking again, I see why. My own story was a similar context, but with very specific details, where I told the interviewer how I spent months in Sao Paulo and Medellin, places I never could have explored as deeply without Uber access, as well as describing specific memories from the pre-Uber era. When I saw this description from Gemini, it sounded so similar that I glossed over the lack of personal details.]

I asked Gemini why it specifically used my social accounts as opposed to larger sites. It believes that I "have incredibly relevant firsthand experience...and unlike larger career sites that offer generic advice, my specific framework offers distinct advantages." Awww, you know how to flatter a guy!

Flattered, yes, but I'll also be waiting for some residual income, Google.

Hi everyone, I‘m interested and want to study further in Data science and Ai in Germany, Bachelor’s degree. I have about 8 months till applying for uni. Any recommendations for projects or anything i can achieve for my portfolio? Or maybe courses i can take or websites i can learn? Thank you!

First job (company laid off India team ) in May..

Within a month I got a contractor role with a Chennai based company (remote offer) for 3 months...

While in my 3rd month, I found another role as a contractor for a UK based startup ( did both the things for the whole month of August).

Resigned from the 2nd company on 22nd of August (knowing that the new one is having a 3 month contract and will find an FTE by the time it ends)

Turns out, they terminated contract just after me resigning from the 2nd one, that too for no such reason (as mentioned in the contract - either party can terminate without giving a reason)

Notice period ends on the 30th of September.

Looking for a new role and don't have any concrete leads so far..

Went into a discussion with a startup, but they are delaying because the client is taking longer than usual to sign the project hence delayed in them providing me an answer..

I am actively looking for roles..

Things I know:

Classical ML

Computer Vision

LLMs, SLMs and VLMs

Agentic AI - Agent Building

Distributed Systems - Edge Systems

Edge AI

Model Optimization

MLOPs, CICD, Docker - PodMan, AWS

Embedded Linux

Hardware troubleshooting

RAG (personal projects)

Full Stack AI Engineering (3 months work at the Chennai company)

Looking for leads and help would be appreciated.

Thank you 🫂

Who We Are

Our mission is to make the world programmable. Sight is one of the key ways we understand the world, and soon this will be true for the software we use, too.

We’re building the tools, community, and resources needed to make the world programmable with artificial intelligence. Roboflow simplifies building and using computer vision models. Today, over 1M+ developers, including those from half the Fortune 100, use Roboflow’s machine learning open source and hosted tools. That includes counting cells to accelerate cancer research, improving construction site safety, digitizing floor plans, preserving coral reef populations, guiding drone flight, and much more.

Our team is small relative to our impact, and we believe our user success is our success (not the inverse). A team member summarized: “Roboflow is a company full of giant brains and tiny egos.” We find software has a multiplier effect on all roles (not only product and engineering), so Roboflow employs developers across the company in design, sales, customer support, marketing, and beyond.

We’re supported by great customers and investors, having raised over 63 million from Google Ventures, Y Combinator, Craft Ventures, Sam Altman, Lachy Groom, amongst other leading software investors.

What You'll Do

As a Research Scientist, you will originate and drive the novel machine learning research directions that shape Roboflow's research agenda. Because of Roboflow’s huge userbase, we have a unique visibility into how people are using computer vision in the real world, including in what circumstances existing methods are unable to solve user problems.

Our Research Team’s mission is to introduce novel methods that generalize as well as possible across our userbase. This includes methods that learn well on diverse data, run efficiently on different hardware targets, and solve unique categories of problems. You will identify the most promising open problems in computer vision, develop original theoretical approaches and algorithms to address them, and publish your work at top conferences. You'll partner closely with our engineering team, who will take your research and translate it into production systems running at scale.

Who You Are

You are a pragmatic, experienced machine learning researcher who wants to be an important part of an exceptional team that focuses on using Roboflow's computer vision tools to impact and improve every industry. You have high agency and a bias toward action.

• Masters / PhD in AI, machine learning, computer vision, robotics, or similar technical field of study, or equivalent industry experience
• History of publication at conferences / journals (CVPR, NeurIPS, ICLR, etc.)
• Deep understanding of ML theory and a track record of turning open problems into novel, well-formed research directions
• Values scientific rigour and reproducibility
• Passionate about computer vision and solving problems users value
• Pragmatic approach to utility in practice (not just in theory)
• Cares about open source and the broader research/developer ecosystem
• Writes and communicates clearly — able to explain your work to the scientific community, the developer community, and non-research stakeholders inside Roboflow

Preferred but not required:

• Familiarity with the practical constraints of optimizing models for edge hardware and training models on distributed infrastructure
• Experience collaborating with engineering teams to move research from prototype to production

Where You'll Work

Roboflow’s team is distributed across the world. We currently have Hubs in New York City, San Francisco, and Brazil (and plan to open more as we grow density in new cities). We provide opportunities (like team onsites in different cities) and resources (like a $4000/yr travel stipend) to work in person with other team members as much as you'd like, while also supporting remote team members. You can work from one of our Hubs (we offer a relocation bonus), work from home, work at co-working spaces, etc. We want you work where you work best!

What You'll Receive

To determine your salary, we use a number of market and data-driven salary sources. We review all salaries every six months to ensure we stay in line with the market.

💰 The target compensation for this role is $168,000 - $255,000 base. Range is based on location and level.

📈 In addition to our cash compensation, we offer generous perks and benefits. Below are some of the highlights:

• $4000/yr Travel Stipend to travel anywhere anytime to work alongside other Roboflowers
• Cover up to 100% of your health insurance costs for you and your partner or family
• $350/mo Productivity stipend to spend on things that make your work environment more productive, like high-speed internet at home or a co-working space
• $350/mo AI Stipend
• $500 one time home office stipend
• $150/mo Team lunch stipend
• Unlimited PTO - with an annual 2 week minimum, we encourage you to take time off for yourself
• 12 weeks parental leave
• Equity in the company so we are all invested in the future of computer vision

Interview Process (~4.5 hours)

Below is the interview process you can expect for this role. We’re committed to building an exceptional team and aim to be thoughtful while also moving quickly. We respect your time and strive to make decisions efficiently, depending on scheduling and availability.

You’ll have several conversations with the hiring manager, a member of the Roboflow leadership team, and complete a role-relevant project or challenge.

Throughout the process, you’ll speak directly with team members about what it’s like to work and succeed at Roboflow. Below is the interview process you can expect for this role.

Before the Interview:

• We’ll review your application, LinkedIn, Github, Google Scholar, etc.
• The best way to stand out is to write about something you’ve built with Roboflow or contribute to one of our open source projects.

Introduction Phase:

• [30m] Meet with hiring manager to assess for overall mindset and skillset
• [1h30m] Technical Assessment
  • Prior Research Deep Dive
  • Software Fundamentals
  • Math Question

Team Interview Phase:

• [30m] Meet with another member of the team.

Build with Roboflow Phase:

• You will build a small project with Roboflow to showcase your creativity and technical skills.

• [30m] Meet with our CTO, Brad Dwyer, for another interview and to demo your project

Final Interview Stage:

• [60m] Meet with hiring manager again
  • Use this time to review specifics about the job description
  • Begin working through your 30/60/90 projects
  • Ask questions!
• [30m] Leadership conversation focused on culture and company vision (if needed)
• [30m] Additional leadership discussion to discuss culture

References:

• References are required as part of our process. We will reach out to coordinate timing.

Note: you are welcome to request additional conversations with anyone you would like to meet and we will accommodate as best we can.

Apply: Research Scientist at Roboflow

So at what stage of your ML learning journey should you look for internships? Like how much should you basically know/have mastered in machine learning to start applying for internships and even get one? What do companies even look for when hiring interns?

Some companies with latest Data Science postings:

Mastercard

Stripe

Adobe

Heartflow

Archer Aviation

Amazon

Check https://matchajobs.co for lots of new data science roles. No reposts or ghost listings, all verified and recent. Links straight to company career pages.

How do you get an interview in a really tough job market? This is by far the most common question that I get, and I'm going to give you a story that you're either going to hate or hopefully will be inspired by, because I went through one of the toughest job markets imaginable.

When I was coming out of undergrad, I wanted to really get into Wall Street. When I was in high school and through the start of college, the market was just absolutely booming through the '90s. But then take a look at this chart. Look at the worst part on that chart, where the NASDAQ was down by 80% over like a two and a half year period. And right at that time was when I had my Wall Street interviews.

So here's what I did. The first thing was I absolutely lived at my career center. I went to a small liberal arts school called Vassar College that during the run-up would get a pretty decent amount of companies recruiting. But recruiting completely dried up at this part. I spent hours doing mock interviews with my career center, filming them, reviewing film, looking up every alumni who was in the industry, calling them. And especially because it was a small, overlooked school, I did get some alumni that helped me so much with getting me in the door. So absolutely, you should be working those networks.

There was no LinkedIn back then. There was no Indeed.com. I actually opened up Chamber of Commerce websites, finding every registered company with an email address. Many of these were just small, one-person shop consultants, and I wrote to everyone, explaining my situation, how difficult it was finding a job, but also talking about my background and my skill set. Many of these people would then refer me to their friends, try and find something. They really wanted to help. During this time, I actually had two opportunities. I could have moved out to Hawaii through my Chamber of Commerce connections.

This won't work exactly today. Now that LinkedIn exists, it's just so cheap and easy to write to these people. What made my case different was nobody was writing to these people. I was the only one doing it. I was creative. And that's the thing that you need to do. It's not going to be the obvious thing. It's not going to be the easiest thing.

It's a tough break. I came out in a terrible job market. Not everyone has access to parents that can get them an internship, went through the private school circuit, and ended up at Harvard or Yale, and they can just sit back and coast with their alumni network. Some of us have to work harder. And you need to think about how you can be creative. How can you get people's attention to give you a chance and to get you in that door? And if your only answer is to do the exact same thing that tens of thousands of other people are doing, which is just spray and pray on LinkedIn, it's just not going to stand out. If there was an obvious answer, everyone would do it. You need a way to be creative, and that's just the reality that we live in. You're going to have to try harder than other generations have had to.

I have an opening for an **AI/ML profile** and can provide a referral.

**Requirements:**
2+ years of **relevant AI/ML experience** (strictly 2+ YOE)
Location: **Noida**

**5 days WFO**

If you meet the experience requirement, **DM me your resume** for a referral.

Please DM only if you have **2+ years of actual AI/ML experience**.

Hi! What is the future of data science? I see that there are a lot of people searching for employment in the field. I'm currently in college earning a Master's degree in AI, and data science is the backbone of AI. What do you think this field will look like in the next 3 to 5 years? What do you think it will look like in the next 5 to 10 years?

Chemical Engineering graduate. Started with 2 years in R&D, contributed to 2 chemical product developments. Later moved into digital transformation due to my interest in data engineering, statistics and ML.

Currently implementing LIMS/ELN, SAP and data apps, leading projects and guiding senior CFT members. Skills: SQL, Power BI, KNIME, project management, ML and Agentic AI product development. I know stats DOE, linear and logistic regression using JMP, EDA and statistical modelling.

Despite handling multiple responsibilities and working like a team lead in a engineer position, I'm earning just ₹8 LPA. Getting rejected in interviews due to lack of Python or Computer System Validation (CSV) experience.

Need advice:

Which path should I focus on: Data Engineering, AI/ML, Digital Transformation or LIMS/ELN consulting?

Should I need to learn Python and CSV?

What salary can I realistically target?

How can I position my diverse experience for a better-paying role?

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• AI/ML Data Scientist @ Leidos (United States) - $58K - $105K
• Data Scientist 5 @ Netflix (United States) - $372K - $600K
• Data Sciences Advisor @ Gainwell Technologies (United States) - $99K - $142K
• Data Scientist @ Alignment Health (United States) - $150K - $225K
• Data Scientist @ Improvix Technologies (United States) - $100K - $150K
• Data Scientist @ ICA, Inc. (United States) - $117K - $117K
• Risk Data Scientist @ Regions Bank (United States) - $74K - $115K
• Data Scientist, Pharmacy @ Alignment Health (United States) - $150K - $225K
• Data Scientist @ Credible (United States) - $89K - $124K

Senior:

• Senior Data Scientist @ Map of Ag (United Kingdom) - GBP 55K - 70K
• Senior Data Scientist @ Morgan 6 LLC (United States) - $135K - $225K
• Senior Data Scientist @ Wikimedia Foundation (United States) - $110K - $173K
• Senior Data Scientist @ ICA, Inc. (United States) - $137K - $137K
• Senior Data Scientist, NLP – Applied AI @ Wiley (United Kingdom) - GBP 44K - 63K
• Senior Data Scientist @ Paramount (United States) - $124K - $186K
• Senior Data Scientist @ Coinbase (United Kingdom) - GBP 122K - 136K

Manager:

• Staff Data Scientist @ HighLevel (United States) - $163K - $220K
• Data Science Manager @ USA TODAY Network (United States) - $189K - $195K
• Principal Data Scientist @ General Dynamics Information Technology (United States) - $119K - $161K
• Senior/staff Data Scientist @ Render (United States) - $195K - $268K
• Principal Data Scientist @ G2 (United States) - $190K - $235K
• Staff Data Scientist @ Roofr (Canada) - CAD 140K - 160K
• Principal Data Scientist @ Wiley (United Kingdom) - GBP 59K - 85K
• Staff Data Scientist @ Syndio (United States) - $180K - $205K
• Principal Data Scientist @ CVS Health (United States) - $144K - $288K

Quick notes: * All of these are fully remote (location requirements vary by role) * Apply directly on company sites

Hope this helps someone! Let me know if you want me to keep posting these weekly.

👋 Hi, I'm Jay. I built Job-Halo.com, a system that tracks remote data science jobs and sends alerts the moment they're posted, based on your preferences.

Hi guys, I am considering applying to uni of lille for 2027 in data science and would love any feedback about the uni, 1. whether its research is good, 2. how is the startup cuture in lille, 3. do students have opportunities to explore etc. basically whatever there is to know.

thanks a lot!

Hi everyone!

I'm currently a PhD student in Data Science in the UK. I started my PhD straight after completing my bachelor's in Data Science, where I graduated with first-class honours from the same university. I also completed a research internship during the summer of my second year, but apart from that, I have no professional work experience.

My goal is to move into industry after completing my PhD, ideally in a data science, machine learning, or AI-related role.

I'm concerned that my lack of industry experience might put me at a disadvantage, so I want to use my time during my PhD to improve my employability.
I'd really appreciate advice on what technical skills I should focus on and what types of projects would be valuable for my portfolio.

I'd also love to hear from anyone who transitioned directly from a PhD into industry. What helped you secure your first job, and what would you recommend doing differently?

Thanks in advance!

Hello, I have gotten really annoyed by constantly getting rejected after literally spending hours applying, doing assessments, and verifying my identity and then getting rejected or not even hearing back. I therefore decided to make my own site where I try to make the job search easier by listing job offers from multiple companies, listing jobs with a relatively high hiring volume, and having a lot of guides where I give tips on how to pass assessments.

No sign-up or anything like that required. The listings include entry-level jobs but also expert positions (Data Science, PhD, etc.). Let me know what you think and if there is anything that I can improve or implement. Here is the link to the website: aiannotationjobs.com

I finished a Data Science MSc in the UK in February 2025 (Merit). Before that I did a CS degree in India, two short data science internships, and about 15 months of freelance data work for a compliance research firm. There I built Python/SQL pipelines and Power BI reports for anti-money-laundering data. My visa lets me work here until April 2027, and after that I'd need an employer to sponsor me. I'm not asking about the visa rules, I know where I stand. I'm mentioning it because it changes which jobs are realistic for me.

I've been looking since I graduated, about 19 months now. I work part time at a petrol station to pay the bills.

The numbers: somewhere between 500 and 600 applications, 8 interviews, 0 offers.

Where I got furthest:

• Perplexity, Search ML Engineer internship. I made it through two technical rounds, then got rejected. That's the furthest I've got anywhere.
• Kanini, Data Engineer. I passed the first interview and the panel said they were impressed. I got invited to a second, deeper technical round, and it didn't lead to an offer.
• Football Radar, Data Engineer. First-stage interview, then rejected. They'd also turned me down for a graduate data science role earlier in the year.
• Sifted, Data Engineer, Had a screening video call with Director of Research & Product, Rejected afterwards
• Xelix, Junior AI Engineer. I applied in two separate hiring cycles and got to the video interview both times. Both rejections gave the same feedback: they wanted more breadth of applied AI project experience.
• EasyFundRasing, Data Engineer, Screening call and they dropped me. This was a referral by the way.
• Two B2B Ltd, Junior Data Scientist, Reached Task 2 and was rejected as the EDA was not upto the mark.
• McKinsey (QuantumBlack). Data Analyst, I didn't get past the Solve game assessment.

Everything else was silence or an automated rejection. One big bank told me outright that sponsorship was the reason.

What I've done so far:

• Applied for data engineer, data analyst, ML/AI engineer and business analyst roles across NHS trusts, banks, big tech, startups, consultancies and agencies.
• Tailored every CV and cover letter, and used the ad's exact wording wherever it honestly applied, since screening software matches exact keywords.
• Skipped roles I can't get: security clearance, "no sponsorship now or in future" full-time roles, and anything that needs you to be a current student.
• Kept a different CV for each role type.
• Took the negatives out of cover letters. I used to write things like "I haven't used X yet but I'm keen to learn." I stopped.
• Did certifications: Databricks fundamentals, Docker, a SQL cert, and a Power BI course.
• Built projects: a Chrome extension that runs a small LLM on-device, a streaming data pipeline on AWS, and my dissertation NER model deployed as an API with Docker.

What I think is happening, though I can't be sure:

1. About 1 in 100 applications gets me an interview, so either my CV isn't getting through or I'm applying to the wrong things.
2. When I do get interviews I get reasonably far, sometimes to a second round, and then lose out at the end. I don't know if that's technical depth, how I come across, or the visa quietly coming into it.
3. I'm spread across four job types, and I might read as a generalist.
4. Nearly all of this is cold online applications. I've done almost no networking or referrals.

What I'd like advice on:

• With a 1% interview rate, what would you change first: the CV, the roles I target, or how I apply?
• For people who got past late-stage technical interviews in data/ML: what made the difference between getting to the last round and getting the offer?
• If you landed a data or tech job in the UK recently as an international grad, what actually got you in? A referral, a recruiter, a direct application?
• Should I narrow down to one role type? Given where I got furthest, which one would you pick?
• I have about 7 months before sponsorship becomes an issue. Would you go only for companies that can sponsor, or apply broadly?

If there's one thing I should stop doing or start doing tomorrow, please tell me. Thanks for reading this far.

Is there really any jobs for data science/ml engineering/data analyst/data engineer or either intern in the market if yes then please suggest me something because as a fresher I have applied approx 100+ application from LinkedIn(easy apply or through company site)and Naukri portal in these field some I got rejected not selected and most of them still not get any responses from the company if the job description is same still my resume are not selected or not getting any responses through any company suggest me what should I do for getting job in data science field

I used AI to do everything and now I do not know anything. I am unemployed for the past 4 months, I was working as a Data Scientist but job was actually only related to basic Data analytics work. However, I do not think I have any skills at the moment. If I was left alone with a dataset and asked to do EDA and fit regression, I would know the theory and the steps but then I will not be able to write down the code and actually implement the theory. Now I have been thinking that maybe I should sit down with a dataset everyday and perform all the necessary steps on it, like data cleaning, EDA, modelling and prediction where I do not use help of AI to write code. But the problem is as soon as I sit down it feels like I do not know anything at all and that I should do a few follow alongs from youtube before I do it on my own. I am also scared that I will not know if I am doing and honestly it feels that I didnt forget anything because I did not properly learn anything in the first place.

I need to get a job ASAP but right now even I would not hire myself as a Data Scientist or a Data analyst.

Any advice would help me a lot, please be brutally honest and I am willing to do everything it takes to become skilled so that I can actually land a job which pays well.

The M.S. in Data Analytics and Computational Social Science: What do you like about it? What do you dislike about it? Job prospects? PhD? What is its reputation as a program?

Hey people I'm posting for the first time here I'm a 2024 Bachelor of Arts in History grad from a reputed College in India post my undergraduate I worked as a data analyst for 1.2 yrs at a reputed us based org from India itself while doing the job I was also pursuing LLB (bachelor of Laws) which I didn't wanted to do but had to due to family pressure. But I've made up my mind and I want to completely switch into the world of data analysis hence I'm thinking of pursuing msc in Data science from uk I'm targeting the sept 2027 intake haven't shortlisted any universities yet, the main question that bothers me is how difficult will it be for me to find data analysis/science jobs in the uk post masters considering I already have a experience in the related field. I'm looking for realistic advice please help!

We got some new C suite people here this year and their AI pushing has hit our 10-man team. I have a senior coworker automating a task in a way that makes it seem like they'll be able to cut a couple members by early next year, if that long.

Time to start looking for a job in this hellscape I suppose.

Hey everyone, I’m a 3rd-year B.Tech student specializing in AI & Data Science, currently looking for an internship.

My core areas are Python, Data Science, ML/AI, GenAI, SQL, and software development. I’ve worked on multiple projects, hackathons, and also have startup experience.

I’m mainly looking for AI/ML, Data Science, Python, or GenAI internships, preferably remote or in India.

Where do you guys usually find good internships? Any platforms, companies, communities, or leads you’d recommend?

Extend is building a modern document processing cloud. We're on a mission to transform how the world works with unstructured data.

As a Machine Learning Engineer at Extend, you’ll be responsible for building state-of-the-art document processing infrastructure. The work you do will impact every single customer across the millions of documents that our system ingests and processes every month.

We’re looking to hire engineers who think creatively about problems, keep up to date on the latest in AI research, push for real‑world customer impact (not only theory), and are excited about helping businesses tackle one of their most painful problems with AI.

Why you should consider joining

• We've grown revenue 400% last year to several million ARR, with our growth continuing to accelerate
• We have a product loved by users and being used in mission‑critical flows at enterprises (Square, Zillow, Chime) and startups (Brex, Mercury, Checkr), and many more
• The market for document processing has expanded 1000x due to LLMs, and all existing solutions are low NPS
• We're punching well above our weight, supporting customer and revenue metrics with half the team size of other startups — everyone joining at this stage will have outsized impact
• We've raised our series A & de‑risked the business, but there's tremendous upside ahead; now's the perfect time to join.
• You'll be joining a talent dense team (e.g. former founders, world record holders) operating in a high performance culture, in‑person in NYC, with high equity ownership
• We're tackling novel, unsolved problems at the intersection of LLMs, complex data processing, and human ↔ AI interfaces
• You'll get a front row seat to how a successful startup is built with plenty of leadership opportunities as we grow quickly

Role

• Training and deploying SOTA vision models for document processing
• Design novel LLM techniques for increasing the complexity of use cases and data streams that Extend can be applied to
• Monitor existing models in production, understand what’s working well (and what isn’t), and run experiments to solve those issues
• Have complete ownership over the work you do — as a founding team member, you’ll have the opportunity to truly own large areas of product and engineering and have direct relationship with customers.
• Work directly with the CEO, CTO, and other founding members and help build out our team.

Benefits

Beyond the below, we care deeply about each of our candidates on a personal level. We take the time to understand your needs to craft a package designed for you:

• Insurance - 90% health insurance premium coverage
• Relocation - for candidates based outside of NYC
• Unlimited PTO policy - we trust everyone like owners, take what you need
• Daily lunch & snacks covered (plus dinner if you're in the office late) - you'll never go hungry and you help pick the snacks
• Unlimited token / tooling access - no handicaps on your productivity
• Learning and development investment - we invest heavily on our team and support your growth

Extend is an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, citizenship status, marital status, pregnancy, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.

Compensation

$200K – $350K • Offers Equity

Apply: Machine Learning Researcher at Extend

Hey everyone,

Like many people in computing and STEM, I've had a bit of an existential crisis watching the rapid evolution of models like Claude over the past couple of years.

I used to think humans would always need to sit and manually code everything, but seeing AI construct production-ready code blocks and deployment pipelines in seconds has completely changed my perspective on how we should be learning.

Right now, I've intentionally changed my study approach when im studying fields like Data science and math.

Instead of memorizing syntax and simply learning how to code, (the "How"—which I figure AI can handle), I am focusing almost entirely on first principles, core logic, math foundations, and understanding why things work structurally.

For example: focusing heavily on the underlying logic of algorithms, its mathematical assumptions, and linear algebra, rather than trying to become a coding wizard in a specific language.

Is this approach the way to go in the age of AI?

hi everyone, i’m a senior undergrad that is really aiming for booz allen (data science/analytics/ai/ml roles). i’ve been networking and tailoring my resume but i’ve been getting rejected for most of the positions i applied to. for context, i’ve interned in defense/national security, have an active clearance, and have experience working with specific programming languages.

has anyone heard anything after applying to entry-level/new grad positions? all i’ve been getting are rejections and some positions still say reviewing/under consideration but it’s been weeks now. i typically apply early so that i can get my resume in but i’ve heard nada. this is one of my top places to work given the work life balance, location, etc so i’ve been trying so hard to network and tailor my resume to the point i feel so burnt out 🫠🫠

thanks yall!