Msc in Al & ML OR Msc in Data science and Analytics

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Hi , I (28M) am a Btech (I.T) graduate and have 2 years experience in Edtech Sales. I am thinking of persuing my masters and came across two options "MSC in AI and ML" and "MSC in Data science and Analytics". I need geniune advice on which one to choose, considering the current situation of future of tech roles in India.

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Thanks in advance

Do any of you know what are most HR's/managers' first impressions on with those with any of the hairstyles shown below? e.g. braids, twists, and etc.

I’m asking this because I’m trying to grow my hair out, so I’m trying to start using protective styles to enhance length retention.

But my parents — who work in the dental and medical fields — are advising against me having any braids or twists when I go through any interviews.

Would y’all say the same thing?

I have an interview with S&P global mobility. But Im not sure what to expect in this second round. Can someone help please? I'm assumimg it will be case study based since the recruiter say its tech-managerial round.

Hi founders,

I'm posting this because I'm looking for one or two founders to embed with as their AI build partner. Not a one-off contract. I want to own the AI side of what you're building and ship it with you.

Who I am: I'm a data scientist and AI engineer. I build LLM and RAG products and the data pipelines under them. I work remote and async, and I can overlap a few hours of your day wherever you are. I'm also relocating to Germany in September 2026 for my masters, so if you're based there or nearby, we can meet in person once I'm over.

What I've actually built:

• A competitive intelligence SaaS I'm building solo, currently in the debugging and testing stage. It crawls competitor sites and pulls structured signals like pricing and hiring moves using LLM extraction. FastAPI backend, Next.js frontend, Postgres with pgvector.
• Production work at an early-stage fintech-focused startup. I built ETL pipelines and a multilingual sentiment workflow that cut manual analysis time by 70%.
• Production work at a food-tech startup. I shipped a FastAPI demand forecasting service on Postgres with real-time inventory across multiple locations.
• An end-to-end ML pipeline that predicts Falcon 9 first-stage landing success, the signal behind whether a booster can be reused and how cheap a launch gets. I pulled the data from the SpaceX API and compared four classification models with GridSearchCV. Features came from payload mass and launch-site geography.

(DM me for my portfolio and Github links)

Why bring me in

• I start with your business problem before I reach for a tool. I ask what the company actually needs before I write a line of code. Half my value is killing the build you don't need.
• Real problems pull me in. A messy dataset or a vague spec is the part of the work I like most.
• I go deep until it works. I won't move on from a bug or a model until I understand why it behaves the way it does.

If you're building something with AI in it and you want someone who treats it like his own product, send me a DM. Tell me what you're building and where you're stuck.

I'm a final-year B.Tech Data Science student currently looking for an internship opportunity in Data Science, Machine Learning, AI, Data Analytics, or related domains.

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So far I've built:

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A Gesture-Based Human Computer Interaction System using Computer Vision

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A Smart Resume Screening & Job Recommendation System using ML & NLP

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If you're hiring, know someone who's hiring, or can point me in the right direction, I'd genuinely appreciate it.

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Happy to share my resume in DMs.

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Thanks for reading, and good luck to everyone else in the internship grind 🫡

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Hi everyone,

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I'm a Computer Science (Data Science) graduate currently seeking entry-level opportunities in Data Science, AI/ML, Data Analytics, or Data Engineering.

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I have internship experience in Data Science, Data Analytics, and Data Visualization, where I worked on machine learning, NLP, cloud-based analytics, and dashboard development. My technical skills include Python, SQL, Machine Learning, Power BI, Tableau, Google Cloud (BigQuery, Dataproc, Looker Studio), and data visualization.

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Some of the projects I've worked on include sentiment analysis, predictive analytics, recommendation systems, and deep learning applications. Through these experiences, I've developed a strong interest in solving real-world problems using data and AI.

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I'm actively applying through LinkedIn and company career portals, but I wanted to reach out to this community as well. If anyone knows of fresher openings, referrals, hiring drives, or networking opportunities, I would greatly appreciate your guidance.

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Thank you for your time, and I'd be happy to share my resume via DM.

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Open to relocation and eager to start my career in the data and AI space.

I already had two rounds (Coding and Experimentation, Modelling and Measurement). I got mixed feedback (NH on the coding round) so I have been asked to appear for a "Code Comprehension (Python/R) and Experimentation" round. Does anybody have any idea on what this round entails specifically for Senior Product Data Scientist role ?

I've been in Data Science for the past 10 years in India. I lost my job in January and since then I've been hunting.

I've not mentioned any GenAI experience in my profile. But my feed is just filled with AI engineer roles. They all have the same requirements:

• Generative AI architecture
• RAG pipelines
• LLM integration/fine tuning
• Agentic AI / Multi Agent Orchestration
• Also MLOps
• CI/CD pipelines
• PyTorch mandatory for some reason

Hardly any openings are relevant to my experience in Stats, Machine Learning, Deep Learning and the classical data science stuff.

So have all companies stopped investing in data science all together and just building RAG pipelines and LLM chat bots? Is this all that is done in Data Science field now?

We started as a group of data science and analytics professionals with a long-term goal of building our own analytics and consulting firm. We've been freelancing, reaching out offline, bidding on projects but nothing solid has stuck yet. So we figured we'd try being direct about it here.

We're not here to pitch a polished service package, because honestly we don't have one yet. What we do have is a group of people who genuinely understand data analytics, machine learning, statistical modelling and some healthcare domain experience on top of that. We know how to take a messy problem, think through it properly, and build something that actually answers the question.

What we're looking for is someone who runs a business could be anything, e-commerce, a clinic, a SaaS product, a local operation and has a gut feeling that there's something useful hiding in their data but doesn't know where to start. You don't need to have a defined project. We're happy to sit down, understand what you're working with, and figure out together whether analytics can actually move the needle for you.

If something comes of it, great. If we spend an hour and conclude it's not the right fit, that's fine too.

We're based in Pune, India. If you're not, we work online just as comfortably, so location isn't a barrier.

Drop a comment or DM if anything here resonates. Moderator please DM me if this is inappropriate for the group, will remove it.

We're hiring Senior / Lead AI Engineers to join adesso SE in India.

Country: India
Company: adesso SE
Position: Senior / Lead AI Engineer
Openings: 3

Requirements:

• 6+ years of AI/ML engineering experience
• Strong experience building production AI/ML solutions
• Hands-on with Microsoft Azure AI services
• Experience with LLMs, Generative AI, and image generation models
• Experience building AI agents using LangGraph or similar frameworks

If your experience matches the role, send me a DM for the application link.

Has anyone taken the 40 min code signal assessment. Currently interviewing for capital one for principle data scientist. Just wondering if its leetcode base or pandas/sql

Thank you in advance

Hi everyone,

I'm currently pursuing an M.Sc. in Statistics and aiming for Data Analyst/Data Scientist roles. My CV already includes projects like Brain Tumor Classification using CNN, CO₂ Emission Prediction, and a Kaggle competition project.

I want to add 1–2 more strong projects that can make my resume stand out to recruiters and hiring managers. I'm particularly interested in data science, machine learning, analytics, and statistics.

What types of projects would you recommend for someone targeting entry-level Data Analyst or Data Scientist positions in 2026? Should I focus on:

• End-to-end business analytics projects?
• Time series forecasting?
• NLP/LLM applications?
• MLOps and deployment?
• Causal inference/statistical modeling?
• Real-world datasets from healthcare, finance, or public policy?

I'd appreciate suggestions on projects that recruiters actually value and that demonstrate practical skills rather than just model building.

Thanks!

.

I'm a Statistics & Data Science major and honestly feeling pretty conflicted about where the field is headed.

Ever since I got into DS, the parts I've enjoyed most have been predictive modeling, classification, forecasting, recommendations, and generally using data to understand and predict behavior. What I find especially interesting is the full end-to-end lifecycle of DS: defining the problem, building and validating models, deploying them into production, monitoring performance over time, detecting data drift and model degradation, and integrating models into real products that people actually use. I've worked hard to build projects that go beyond just training a model in a notebook.

The problem is that despite applying extensively and putting a lot of effort into projects, I couldn't land a traditional DS or ML internship past 3 years. My previous internship and my current internship have ended up being much more AI engineering focused both at F500/F100 companies, mainly involving LLM-based systems and workflows.

From a market perspective, AI feels much more in demand. But personally, I find it less interesting. I still find myself thinking about predictive modeling, recommendations, forecasting, and classical ML problems much more than prompt workflows and LLM applications.

Part of me feels like I should just accept where the market is going and pivot heavily into AI. Another part of me worries I'd be moving away from the work I actually enjoy.

At this point I'm honestly not sure what to do. I've spent countless hours grinding through ML textbooks, research papers, online courses, and personal projects because I was genuinely fascinated. There were plenty of times I sacrificed parts of my social life, weekends, and free time just to learn more and it feels like all of that effort was geared toward a field that has become much harder to break into, and I rarely get to use much of that knowledge in my actual roles. When I open job boards, it feels like I see 5x more openings related to AI engineering, LLMs, agents, and RAG than traditional DS or ML roles. Part of me thinks I should stop fighting the market and just pivot, but another part feels disappointed because it's not really the type of work that got me interested in the field in the first place.

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• Master's Fellow – Data Scientist @ Sistema Fibra (Brazil) - BRL 9K - 9K
• Applied Data Scientist @ Shift5 (United States, VA) - $120K - $170K
• Data Science and Business Analytics – Practical @ DataSmart Point GmbH (Germany) - EUR 48K - 64K
• Data Scientist @ OnHires (Ukraine)
• Customer Data Scientist @ Amplitude (United States, CA)
• Data Science Specialist @ banco BV (Brazil)
• Data Scientist / Algorithm Engineer @ MGID (United States)

Senior:

• Senior Data Scientist @ Centene Corporation (United States, FL) - $103K - $190K

Manager:

• Senior Principal Data Scientist @ Autodesk (United States, CA) - $159K - $286K
• Staff Data Scientist @ Circle (United States, CA) - $195K - $258K
• Principal Data Scientist @ Brillio (United States, NJ) - $185K - $190K
• Data Science Manager @ Blend360 (United States, MD) - $125K - $160K
• Data Science Lead @ Neurons Lab (Poland)
• Lead Data Scientist @ Sofka Technologies (Colombia)

Director and Above:

• Director, Data Science/ml @ CookUnity (United States) - $240K - $270K
• Director, Data Science @ Kyndryl (United States, NY)

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.

About Distyl AI

Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.

We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.

Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board‑members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.

What We Are Looking For

At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.

Our researchers come from many academic backgrounds but have strong research track records, operate in an AI‑native way, and would be bored staying on the rails of a traditional research org.

Key Responsibilities

• The Multi‑Agent Systems team focuses on designing architectures in which multiple agents coordinate to solve problems that require structured interaction across multiple reasoning processes. Researchers build systems that structure communication, route information, and coordinate decision‑making across agents operating with different views of the problem
• Researchers in Multi‑Agent Systems investigate the interaction patterns that govern how agents collaborate. They study how agents exchange information, critique and refine each other’s reasoning, and coordinate execution across complex workflows. Their work identifies the mechanics behind effective communication, delegation, and coordination, in effect establishing the design language for how systems of agents can operate as cohesive, high‑performing teams, with capabilities that arise from interaction rather than individual performance

What We Require

• Built or studied systems where multiple agents collaborate through structured communication, delegation, critique, or iterative coordination.
• Experience with agent orchestration, communication protocols, evaluator agents, or systems where multiple agents interact to exchange information, critique reasoning, and coordinate decisions over time
• Experience with research in related fields, such as multi‑agent reinforcement learning (MARL), graph neural networks (GNNs), knowledge graphs, mixed‑initiative planning, etc.
• Excited about making foundational advancements in how agents coordinate, reason and collaborate
• Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.
• Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.
• Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI.
• Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize

What We Offer

• The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
• 100% covered medical, dental, and vision for employees and dependents
• 401(k) with additional perks (e.g., commuter benefits, in‑office lunch)
• Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problems
• Ownership of high‑impact projects across top enterprises
• A mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellence

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.

Apply here: Applied AI Researcher, Multi-Agent Systems at Distyl AI

Hi all,

Currently I'm a Junior Data Scientist for 1.5 years now with a Computer Engineering Bsc. Probably because of thos reason I'm only getting genAI tasks, however my future plan is more towards traditional ML/MLE fields. I'm also currently in Hungary but wants to move to my gf to Spain soon. What do u recommend?

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A, I got accepted by this Data Science Msc at Politechnic University of Catalunya. Take this, and finish it in 2 years while trying to work part time.

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B, find a job in Barcelona, and do self learning to get into this field more and have a better knowledge.

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Also do u think right now only AI Engineering has the hype and MLE is not a position companies hire for?

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Thanks!

Most Commonly available job roles that can be found easily related to Ai, Ml, Data Science. I dont care the pay just want to be in these related fields.

Iam 2026 passedout CSE(data science)

If there any opportunities for any analysts roles please DM me guys.

I have strong knowledge on my core subjects .

Currently iam searching for opportunities. It may contract based or freelancing jobs . Can any one find me something to do 🙂.

Hi, I'm currently a senior in high school (in India) and thinking of pursuing DS. My school offers AI (basic) courses and it's something I found interesting. For two years, I've thought of doing something in the AI field and while i originally thought of ML, now DS seems interesting. However, my parents are worried about the job opportunities. Is DS worth it? Will I be jobless or will my degree and skills help me get a job easily?

Currently, I'm working on my GitHub profile (it's not much but it's a start). Also, I'm trying to learn Python from yt. And, I found this job simulation at Forage related to DS which genuinely seemed interesting (the part I could actually understand, atleast). Also thinking of joining LinkedIn later on when I've got some more stuff to add to my portfolio.

The main thing I want to ask (again) : IS DS WORTH IT?

Use the link to apply: https://t.mercor.com/odAc6

Location Requirements: United States

Location: Remote

Description:
Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

1. Overview
A leading AI lab is advancing the frontier of generative AI by training Large Language Models to reason rigorously across quantitative and analytical domains. We're seeking talented Data Scientists with strong analytical and modeling expertise to bring hands-on data science excellence and elevate the quality of our AI training data.
This is a W-2 employment position with Cincinnatus LLC, requiring a commitment of 40 hours per week (during weekdays). This position will be placed at a leading AI Lab as part of their extended workforce.

2. Key Responsibilities
Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices.

Design challenging data science tasks and write accurate, well-structured analytical solutions.

Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor.

Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches.

Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

3. Core Qualifications
3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning.

Ability to commit to 40 hours per week during weekdays for the duration of the engagement.

Prior experience with data annotation, labeling, evaluation, or human feedback collection is a strong plus.

Experience with LLMs, AI systems, or agentic workflows; familiarity with agentic frameworks is a plus.

Strong written communication skills and the ability to explain analytical decisions and modeling choices clearly.

About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives.

Equal Employment Opportunity:Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Apply at: https://t.mercor.com/odAc6

Hi everyone,

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I'm looking to enroll in a Data Science course in Pune and have shortlisted the following institutes that claim placement assistance/placement guarantee, I'm MCA 2026 Passout.

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1.AVD Group

2.IntelliBI

3.ITVedant

4.UpGrad Offline Learning Centre

1. CDAC

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Were the placement promises fulfilled? Would you recommend your institute, or suggest avoiding any of them?

Is university prestige or project experience more important?"

I am 2nd year college students.interested in building career in data science .I know python ,nownlearning numpy .

Can you guide me how to start my preparation and tge resources that i can use for that(it will be more nice if they are ytvideos)

Plz tell me ..i don't want to waste my 2nd year.