Machine learning powers so many things around us – from recommendation systems to self-driving cars!
But understanding the different types of algorithms can be tricky.
This is a quick and easy guide to the four main categories: Supervised, Unsupervised, Semi-Supervised, and Reinforcement Learning.
𝟏. 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
In supervised learning, the model learns from examples that already have the answers (labeled data). The goal is for the model to predict the correct result when given new data.
𝐒𝐨𝐦𝐞 𝐜𝐨𝐦𝐦𝐨𝐧 𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ Linear Regression – For predicting continuous values, like house prices.
➡️ Logistic Regression – For predicting categories, like spam or not spam.
➡️ Decision Trees – For making decisions in a step-by-step way.
➡️ K-Nearest Neighbors (KNN) – For finding similar data points.
➡️ Random Forests – A collection of decision trees for better accuracy.
➡️ Neural Networks – The foundation of deep learning, mimicking the human brain.
𝟐. 𝐔𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
With unsupervised learning, the model explores patterns in data that doesn’t have any labels. It finds hidden structures or groupings.
𝐒𝐨𝐦𝐞 𝐩𝐨𝐩𝐮𝐥𝐚𝐫 𝐮𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ K-Means Clustering – For grouping data into clusters.
➡️ Hierarchical Clustering – For building a tree of clusters.
➡️ Principal Component Analysis (PCA) – For reducing data to its most important parts.
➡️ Autoencoders – For finding simpler representations of data.
𝟑. 𝐒𝐞𝐦𝐢-𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
This is a mix of supervised and unsupervised learning. It uses a small amount of labeled data with a large amount of unlabeled data to improve learning.
𝐂𝐨𝐦𝐦𝐨𝐧 𝐬𝐞𝐦𝐢-𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ Label Propagation – For spreading labels through connected data points.
➡️ Semi-Supervised SVM – For combining labeled and unlabeled data.
➡️ Graph-Based Methods – For using graph structures to improve learning.
𝟒. 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
In reinforcement learning, the model learns by trial and error. It interacts with its environment, receives feedback (rewards or penalties), and learns how to act to maximize rewards.
𝐏𝐨𝐩𝐮𝐥𝐚𝐫 𝐫𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ Q-Learning – For learning the best actions over time.
➡️ Deep Q-Networks (DQN) – Combining Q-learning with deep learning.
➡️ Policy Gradient Methods – For learning policies directly.
➡️ Proximal Policy Optimization (PPO) – For stable and effective learning.
ENJOY LEARNING 👍👍
But understanding the different types of algorithms can be tricky.
This is a quick and easy guide to the four main categories: Supervised, Unsupervised, Semi-Supervised, and Reinforcement Learning.
𝟏. 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
In supervised learning, the model learns from examples that already have the answers (labeled data). The goal is for the model to predict the correct result when given new data.
𝐒𝐨𝐦𝐞 𝐜𝐨𝐦𝐦𝐨𝐧 𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ Linear Regression – For predicting continuous values, like house prices.
➡️ Logistic Regression – For predicting categories, like spam or not spam.
➡️ Decision Trees – For making decisions in a step-by-step way.
➡️ K-Nearest Neighbors (KNN) – For finding similar data points.
➡️ Random Forests – A collection of decision trees for better accuracy.
➡️ Neural Networks – The foundation of deep learning, mimicking the human brain.
𝟐. 𝐔𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
With unsupervised learning, the model explores patterns in data that doesn’t have any labels. It finds hidden structures or groupings.
𝐒𝐨𝐦𝐞 𝐩𝐨𝐩𝐮𝐥𝐚𝐫 𝐮𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ K-Means Clustering – For grouping data into clusters.
➡️ Hierarchical Clustering – For building a tree of clusters.
➡️ Principal Component Analysis (PCA) – For reducing data to its most important parts.
➡️ Autoencoders – For finding simpler representations of data.
𝟑. 𝐒𝐞𝐦𝐢-𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
This is a mix of supervised and unsupervised learning. It uses a small amount of labeled data with a large amount of unlabeled data to improve learning.
𝐂𝐨𝐦𝐦𝐨𝐧 𝐬𝐞𝐦𝐢-𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ Label Propagation – For spreading labels through connected data points.
➡️ Semi-Supervised SVM – For combining labeled and unlabeled data.
➡️ Graph-Based Methods – For using graph structures to improve learning.
𝟒. 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
In reinforcement learning, the model learns by trial and error. It interacts with its environment, receives feedback (rewards or penalties), and learns how to act to maximize rewards.
𝐏𝐨𝐩𝐮𝐥𝐚𝐫 𝐫𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:
➡️ Q-Learning – For learning the best actions over time.
➡️ Deep Q-Networks (DQN) – Combining Q-learning with deep learning.
➡️ Policy Gradient Methods – For learning policies directly.
➡️ Proximal Policy Optimization (PPO) – For stable and effective learning.
ENJOY LEARNING 👍👍
Data Scientist – Fraud Risk🚀
📍 Hyderabad | Gurgaon | Bangalore
Do you have a passion for fighting fraud with data & machine learning? 💡
We’re looking for Data Scientists / Sr. Data Scientists who love solving complex problems and want to make an impact in the world of Fraud Risk & Analytics.
✨ What You’ll Work On
🔹 Build & deploy advanced ML models to detect and prevent Payment Fraud
🔹 Dive deep into SQL + Python + PySpark to analyze large datasets
🔹 Spot hidden fraud patterns & create smarter prevention strategies
🔹 Collaborate with cross-functional teams to continuously improve detection systems
👩💻 What We’re Looking For
✔️ 2.5–5 years’ experience in SQL + ML (Classification & Regression Models)
✔️ Strong skills in Excel, SQL, PySpark & Python
✔️ Hands-on experience in fraud detection models (a big plus!)
✔️ Immediate joiners (or <30 days’ notice) ONLY
📩 Ready to fight fraud with us?
Share your resume at anupama.rao@straive.com
📍 Hyderabad | Gurgaon | Bangalore
Do you have a passion for fighting fraud with data & machine learning? 💡
We’re looking for Data Scientists / Sr. Data Scientists who love solving complex problems and want to make an impact in the world of Fraud Risk & Analytics.
✨ What You’ll Work On
🔹 Build & deploy advanced ML models to detect and prevent Payment Fraud
🔹 Dive deep into SQL + Python + PySpark to analyze large datasets
🔹 Spot hidden fraud patterns & create smarter prevention strategies
🔹 Collaborate with cross-functional teams to continuously improve detection systems
👩💻 What We’re Looking For
✔️ 2.5–5 years’ experience in SQL + ML (Classification & Regression Models)
✔️ Strong skills in Excel, SQL, PySpark & Python
✔️ Hands-on experience in fraud detection models (a big plus!)
✔️ Immediate joiners (or <30 days’ notice) ONLY
📩 Ready to fight fraud with us?
Share your resume at anupama.rao@straive.com
❤1
📌SONY is hiring for Machine Learning Role
Experience: 0 - 2 years
Apply here: https://www.linkedin.com/jobs/view/4290651291/
Experience: 0 - 2 years
Apply here: https://www.linkedin.com/jobs/view/4290651291/
Linkedin
Sony Research India hiring Machine Learning Consultant in India | LinkedIn
Posted 6:16:05 AM. Sony Research India is driving cutting-edge research and development in various locations around…See this and similar jobs on LinkedIn.
❤2
Godrej Capital is hiring Data Scientist 🚀
Experience : 2 Years
Location : Mumbai
Apply link : Check out this job at Godrej Capital: https://www.linkedin.com/jobs/view/4292342820
Experience : 2 Years
Location : Mumbai
Apply link : Check out this job at Godrej Capital: https://www.linkedin.com/jobs/view/4292342820
Linkedin
Godrej Capital hiring Data Scientist in Mumbai, Maharashtra, India | LinkedIn
Posted 6:18:48 AM. Godrej Capital is a subsidiary of Godrej Industries and is the holding company for Godrej Housing…See this and similar jobs on LinkedIn.
Step-by-Step Roadmap to Learn Data Science in 2025:
Step 1: Understand the Role
A data scientist in 2025 is expected to:
Analyze data to extract insights
Build predictive models using ML
Communicate findings to stakeholders
Work with large datasets in cloud environments
Step 2: Master the Prerequisite Skills
A. Programming
Learn Python (must-have): Focus on pandas, numpy, matplotlib, seaborn, scikit-learn
R (optional but helpful for statistical analysis)
SQL: Strong command over data extraction and transformation
B. Math & Stats
Probability, Denoscriptive & Inferential Statistics
Linear Algebra & Calculus (only what's necessary for ML)
Hypothesis testing
Step 3: Learn Data Handling
Data Cleaning, Preprocessing
Exploratory Data Analysis (EDA)
Feature Engineering
Tools: Python (pandas), Excel, SQL
Step 4: Master Machine Learning
Supervised Learning: Linear/Logistic Regression, Decision Trees, Random Forests, XGBoost
Unsupervised Learning: K-Means, Hierarchical Clustering, PCA
Deep Learning (optional): Use TensorFlow or PyTorch
Evaluation Metrics: Accuracy, AUC, Confusion Matrix, RMSE
Step 5: Learn Data Visualization & Storytelling
Python (matplotlib, seaborn, plotly)
Power BI / Tableau
Communicating insights clearly is as important as modeling
Step 6: Use Real Datasets & Projects
Work on projects using Kaggle, UCI, or public APIs
Examples:
Customer churn prediction
Sales forecasting
Sentiment analysis
Fraud detection
Step 7: Understand Cloud & MLOps (2025+ Skills)
Cloud: AWS (S3, EC2, SageMaker), GCP, or Azure
MLOps: Model deployment (Flask, FastAPI), CI/CD for ML, Docker basics
Step 8: Build Portfolio & Resume
Create GitHub repos with well-documented code
Post projects and blogs on Medium or LinkedIn
Prepare a data science-specific resume
Step 9: Apply Smartly
Focus on job roles like: Data Scientist, ML Engineer, Data Analyst → DS
Use platforms like LinkedIn, Glassdoor, Hirect, AngelList, etc.
Practice data science interviews: case studies, ML concepts, SQL + Python coding
Step 10: Keep Learning & Updating
Follow top newsletters: Data Elixir, Towards Data Science
Read papers (arXiv, Google Scholar) on trending topics: LLMs, AutoML, Explainable AI
Upskill with certifications (Google Data Cert, Coursera, DataCamp, Udemy)
Free Resources to learn Data Science
Kaggle Courses: https://www.kaggle.com/learn
CS50 AI by Harvard: https://cs50.harvard.edu/ai/
Fast.ai: https://course.fast.ai/
Google ML Crash Course: https://developers.google.com/machine-learning/crash-course
Data Science Learning Series: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D/998
Data Science Books: https://news.1rj.ru/str/datalemur
React ❤️ for more
Step 1: Understand the Role
A data scientist in 2025 is expected to:
Analyze data to extract insights
Build predictive models using ML
Communicate findings to stakeholders
Work with large datasets in cloud environments
Step 2: Master the Prerequisite Skills
A. Programming
Learn Python (must-have): Focus on pandas, numpy, matplotlib, seaborn, scikit-learn
R (optional but helpful for statistical analysis)
SQL: Strong command over data extraction and transformation
B. Math & Stats
Probability, Denoscriptive & Inferential Statistics
Linear Algebra & Calculus (only what's necessary for ML)
Hypothesis testing
Step 3: Learn Data Handling
Data Cleaning, Preprocessing
Exploratory Data Analysis (EDA)
Feature Engineering
Tools: Python (pandas), Excel, SQL
Step 4: Master Machine Learning
Supervised Learning: Linear/Logistic Regression, Decision Trees, Random Forests, XGBoost
Unsupervised Learning: K-Means, Hierarchical Clustering, PCA
Deep Learning (optional): Use TensorFlow or PyTorch
Evaluation Metrics: Accuracy, AUC, Confusion Matrix, RMSE
Step 5: Learn Data Visualization & Storytelling
Python (matplotlib, seaborn, plotly)
Power BI / Tableau
Communicating insights clearly is as important as modeling
Step 6: Use Real Datasets & Projects
Work on projects using Kaggle, UCI, or public APIs
Examples:
Customer churn prediction
Sales forecasting
Sentiment analysis
Fraud detection
Step 7: Understand Cloud & MLOps (2025+ Skills)
Cloud: AWS (S3, EC2, SageMaker), GCP, or Azure
MLOps: Model deployment (Flask, FastAPI), CI/CD for ML, Docker basics
Step 8: Build Portfolio & Resume
Create GitHub repos with well-documented code
Post projects and blogs on Medium or LinkedIn
Prepare a data science-specific resume
Step 9: Apply Smartly
Focus on job roles like: Data Scientist, ML Engineer, Data Analyst → DS
Use platforms like LinkedIn, Glassdoor, Hirect, AngelList, etc.
Practice data science interviews: case studies, ML concepts, SQL + Python coding
Step 10: Keep Learning & Updating
Follow top newsletters: Data Elixir, Towards Data Science
Read papers (arXiv, Google Scholar) on trending topics: LLMs, AutoML, Explainable AI
Upskill with certifications (Google Data Cert, Coursera, DataCamp, Udemy)
Free Resources to learn Data Science
Kaggle Courses: https://www.kaggle.com/learn
CS50 AI by Harvard: https://cs50.harvard.edu/ai/
Fast.ai: https://course.fast.ai/
Google ML Crash Course: https://developers.google.com/machine-learning/crash-course
Data Science Learning Series: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D/998
Data Science Books: https://news.1rj.ru/str/datalemur
React ❤️ for more
❤5👍1
🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the most in-demand AI skill in today’s job market: building autonomous AI systems.
In Ready Tensor’s free, project-first program, you’ll create three portfolio-ready projects using 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, and vector databases — and deploy production-ready agents that employers will notice.
Includes guided lectures, videos, and code.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.
👉 Apply now: https://go.readytensor.ai/cert-610-agentic-ai-certification
React ❤️ for more free resources
Master the most in-demand AI skill in today’s job market: building autonomous AI systems.
In Ready Tensor’s free, project-first program, you’ll create three portfolio-ready projects using 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, and vector databases — and deploy production-ready agents that employers will notice.
Includes guided lectures, videos, and code.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.
👉 Apply now: https://go.readytensor.ai/cert-610-agentic-ai-certification
React ❤️ for more free resources
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We're Hiring - Computer Vision Engineers & Al
Connect
We're expanding our team and looking for skilled
professionals to join us in building intelligent,
real-world solutions
Requirements:
2+ years of hands-on experience in Al/ML or
Computer Vision roles
Strong proficiency in Python
Solid experience with:
Open Cv
Pytourch
Image Classification
YOLO and object detection
Transfer Learning
Machine Learning frameworks and pipelines
Location: Mumbai (On-site)
Working Days: Monday to Friday (Weekends Off)
Votice Period: Immediate to 15 days
We offer a collaborative, innovation-driven work
culture where your contributions directly shape
impactful Al solutions
Send your resume to chitra.borkar@acxtech.co.in
Connect
We're expanding our team and looking for skilled
professionals to join us in building intelligent,
real-world solutions
Requirements:
2+ years of hands-on experience in Al/ML or
Computer Vision roles
Strong proficiency in Python
Solid experience with:
Open Cv
Pytourch
Image Classification
YOLO and object detection
Transfer Learning
Machine Learning frameworks and pipelines
Location: Mumbai (On-site)
Working Days: Monday to Friday (Weekends Off)
Votice Period: Immediate to 15 days
We offer a collaborative, innovation-driven work
culture where your contributions directly shape
impactful Al solutions
Send your resume to chitra.borkar@acxtech.co.in
❤2
🚀 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the hottest skill in tech: building intelligent AI systems that think and act independently.
Join Ready Tensor’s free, hands-on program to create three portfolio-grade projects: RAG systems → Multi-agent workflows → Production deployment.
𝗘𝗮𝗿𝗻 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 and 𝗴𝗲𝘁 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝗯𝘆 𝘁𝗼𝗽 𝗔𝗜 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗿𝘀.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.
👉 Join today: https://go.readytensor.ai/cert-610-agentic-ai-certification
Master the hottest skill in tech: building intelligent AI systems that think and act independently.
Join Ready Tensor’s free, hands-on program to create three portfolio-grade projects: RAG systems → Multi-agent workflows → Production deployment.
𝗘𝗮𝗿𝗻 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 and 𝗴𝗲𝘁 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝗯𝘆 𝘁𝗼𝗽 𝗔𝗜 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗿𝘀.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.
👉 Join today: https://go.readytensor.ai/cert-610-agentic-ai-certification
❤2
Goodspace ai is hiring Data Analyst 🚀
Freshers are eligible ✅
Location : Noida
Apply link : https://goodspace.ai/jobs/Data-Analyst?id=29388&applySource=LinkedIn_Jobs&source=campaign_LinkedIn_Jobs-Archana_Data_Analyst-29388
Freshers are eligible ✅
Location : Noida
Apply link : https://goodspace.ai/jobs/Data-Analyst?id=29388&applySource=LinkedIn_Jobs&source=campaign_LinkedIn_Jobs-Archana_Data_Analyst-29388
GoodSpace AI
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MakeMyTrip is hiring Product Analyst 🚀
Min. Experience : 2 Years
Location : Gurugram
Apply link : Check out this job at MakeMyTrip: https://www.linkedin.com/jobs/view/4298160825
Min. Experience : 2 Years
Location : Gurugram
Apply link : Check out this job at MakeMyTrip: https://www.linkedin.com/jobs/view/4298160825
Linkedin
MakeMyTrip hiring Product Analyst in Gurugram, Haryana, India | LinkedIn
Posted 7:52:02 AM. About the Opportunity:Role : Product AnalystLevel : Senior Executive/ Assistant ManagerLocation :…See this and similar jobs on LinkedIn.
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ITC Infotech is hiring Data Analyst 🚀
Min. Experience : 2 Years
Location : Bangalore
Apply link : Check out this job at ITC Infotech: https://www.linkedin.com/jobs/view/4297814963
Min. Experience : 2 Years
Location : Bangalore
Apply link : Check out this job at ITC Infotech: https://www.linkedin.com/jobs/view/4297814963
Linkedin
ITC Infotech hiring Data Analyst in Bengaluru, Karnataka, India | LinkedIn
Posted 8:18:23 AM. Urgently hiring at ITC Infotech for the below mentioned requirement.
Role - Data AnalystExperience…See this and similar jobs on LinkedIn.
Role - Data AnalystExperience…See this and similar jobs on LinkedIn.
❤1
Master the hottest skill in tech: building intelligent AI systems that think and act independently.
Join Ready Tensor’s free, hands-on program to build smart chatbots, AI assistants and multi-agent systems.
𝗘𝗮𝗿𝗻 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 and 𝗴𝗲𝘁 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝗯𝘆 𝘁𝗼𝗽 𝗔𝗜 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗿𝘀.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.
👉 Join today: https://go.readytensor.ai/cert-610-agentic-ai-certification
React ❤️ for more free resources
Join Ready Tensor’s free, hands-on program to build smart chatbots, AI assistants and multi-agent systems.
𝗘𝗮𝗿𝗻 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 and 𝗴𝗲𝘁 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝗯𝘆 𝘁𝗼𝗽 𝗔𝗜 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗿𝘀.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.
👉 Join today: https://go.readytensor.ai/cert-610-agentic-ai-certification
React ❤️ for more free resources
❤2
Forwarded from AI Jobs | Artificial Intelligence
🚀 Hiring: AI / ML Engineer
📍 Princeton, NJ (Hybrid – 2 days onsite)
Apply: rahul.g@laibatechnology.com
We are looking for a hands-on AI/ML Engineer to design, build, and deploy cutting-edge ML & LLM solutions in production.
Key Responsibilities:
🔹 Build & optimize ML/Deep Learning models for large-scale data
🔹 Deploy & monitor ML/LLM models using APIs & cloud platforms
🔹 Manage AKS clusters, containerized workloads & CI/CD pipelines
🔹 Implement model governance, versioning & reproducibility (MLflow, Azure DevOps)
🔹 Collaborate with data scientists & domain experts for real-world impact
Tech Stack:
✅ Python | Docker | Kubernetes | Terraform | Azure ML | Azure OpenAI | AKS | MLflow | Prometheus | Grafana
Must-Haves:
📌 Strong experience in ML/LLMs (fine-tuning, prompt engineering, deployment)
📌 Cloud expertise in Azure ecosystem (ML, AKS, OpenAI, DevOps)
📌 Proven skills in scalable ML infrastructure & CI/CD automation
📍 Princeton, NJ (Hybrid – 2 days onsite)
Apply: rahul.g@laibatechnology.com
We are looking for a hands-on AI/ML Engineer to design, build, and deploy cutting-edge ML & LLM solutions in production.
Key Responsibilities:
🔹 Build & optimize ML/Deep Learning models for large-scale data
🔹 Deploy & monitor ML/LLM models using APIs & cloud platforms
🔹 Manage AKS clusters, containerized workloads & CI/CD pipelines
🔹 Implement model governance, versioning & reproducibility (MLflow, Azure DevOps)
🔹 Collaborate with data scientists & domain experts for real-world impact
Tech Stack:
✅ Python | Docker | Kubernetes | Terraform | Azure ML | Azure OpenAI | AKS | MLflow | Prometheus | Grafana
Must-Haves:
📌 Strong experience in ML/LLMs (fine-tuning, prompt engineering, deployment)
📌 Cloud expertise in Azure ecosystem (ML, AKS, OpenAI, DevOps)
📌 Proven skills in scalable ML infrastructure & CI/CD automation
❤2🔥1
Hiring: Data Scientist (ML & Gen AI)
📍 Location: Hyderabad / Bangalore (Hybrid, 5 days)
💼 Experience: 3+ years
💰 CTC: Up to ₹21 LPA
We’re looking for a skilled Data Scientist to work on ML models & Gen AI projects.
✅ Strong ML/Gen AI experience
✅ Python, SQL, TensorFlow/PyTorch
✅ Cloud (AWS/GCP/Azure) knowledge
📩 Apply now: [https://lnkd.in/grzQ3US6]
📍 Location: Hyderabad / Bangalore (Hybrid, 5 days)
💼 Experience: 3+ years
💰 CTC: Up to ₹21 LPA
We’re looking for a skilled Data Scientist to work on ML models & Gen AI projects.
✅ Strong ML/Gen AI experience
✅ Python, SQL, TensorFlow/PyTorch
✅ Cloud (AWS/GCP/Azure) knowledge
📩 Apply now: [https://lnkd.in/grzQ3US6]
lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn
👍1
Cyient is hiring!
Position: Data Scientist - Junior
Qualifications: Bachelor’s/ Master’s Degree
Salary: 6 - 11 LPA (Expected)
Experience: Freshers/ Experienced
Location: Hyderabad, India
📌Apply Now: https://careers.cyient.com/cyient/jobview/data-scientist-junior-hyderabad-india-2025081312010289?id=678417
Position: Data Scientist - Junior
Qualifications: Bachelor’s/ Master’s Degree
Salary: 6 - 11 LPA (Expected)
Experience: Freshers/ Experienced
Location: Hyderabad, India
📌Apply Now: https://careers.cyient.com/cyient/jobview/data-scientist-junior-hyderabad-india-2025081312010289?id=678417
❤3
IBM Summer Internship Program!
Position: Research Intern - AI
Qualifications: Bachelor’s Degree
Salary: 30K - 50K Per Month (Expected)
Batch: 2024/ 2025/ 2026/ 2027
Experience: Freshers
Location: Bangalore; Gurgaon, India (Hybrid)
📌Apply Now: https://ibmglobal.avature.net/en_US/careers/JobDetail?jobId=59041&source=WEB_Search_INDIA
👉WhatsApp Channel: https://whatsapp.com/channel/0029VaxngnVInlqV6xJhDs3m
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
Position: Research Intern - AI
Qualifications: Bachelor’s Degree
Salary: 30K - 50K Per Month (Expected)
Batch: 2024/ 2025/ 2026/ 2027
Experience: Freshers
Location: Bangalore; Gurgaon, India (Hybrid)
📌Apply Now: https://ibmglobal.avature.net/en_US/careers/JobDetail?jobId=59041&source=WEB_Search_INDIA
👉WhatsApp Channel: https://whatsapp.com/channel/0029VaxngnVInlqV6xJhDs3m
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
❤4
Uber is hiring!
Position: Data Scientist, Data Science
Qualification: Bachelor's/ Master’s Degree
Salary: 16 - 46 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore, India
📌Apply Now: https://www.uber.com/global/en/careers/list/148160/?uclick_id=191f4c10-ec74-4d28-861c-ecce1809c397
👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
Position: Data Scientist, Data Science
Qualification: Bachelor's/ Master’s Degree
Salary: 16 - 46 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore, India
📌Apply Now: https://www.uber.com/global/en/careers/list/148160/?uclick_id=191f4c10-ec74-4d28-861c-ecce1809c397
👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
❤3
Forwarded from Data Analyst Jobs
𝐇𝐒𝐁𝐂 - 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐈𝐧𝐭𝐞𝐫𝐧𝐬𝐡𝐢𝐩!
Position: Intern - Data Science
Qualifications: Bachelor’s/ Master’s Degree
Salary: 4 - 8 LPA (Expected)
Experience: Freshers
Location: Benglore
📌Apply Now: https://mycareer.hsbc.com/en_GB/external/PipelineDetail/Intern-Data-Science/286724
👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
Position: Intern - Data Science
Qualifications: Bachelor’s/ Master’s Degree
Salary: 4 - 8 LPA (Expected)
Experience: Freshers
Location: Benglore
📌Apply Now: https://mycareer.hsbc.com/en_GB/external/PipelineDetail/Intern-Data-Science/286724
👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
❤1
Uber Internship!
Position: Data Science Internship
Qualifications: Bachelor’s/ Master’s Degree
Salary: ₹ 8.4 LPA (Expected)
Batch: 2025/ 2026
Experience: Freshers
Location: Bangalore/ Hyderabad
📌Apply Now: https://university-uber.icims.com/jobs/148994/job?mobile=true&width=360&height=708&bga=true&needsRedirect=false&jan1offset=330&jun1offset=330
👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
Position: Data Science Internship
Qualifications: Bachelor’s/ Master’s Degree
Salary: ₹ 8.4 LPA (Expected)
Batch: 2025/ 2026
Experience: Freshers
Location: Bangalore/ Hyderabad
📌Apply Now: https://university-uber.icims.com/jobs/148994/job?mobile=true&width=360&height=708&bga=true&needsRedirect=false&jan1offset=330&jun1offset=330
👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5
All the best 👍👍
❤3