Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Hyderabad Location-24th Aug 2025(Sunday)

Interested candidates share your CV at umaparvathyc@hexaware.com

Open Positions:
AI Engineer
Lead Data Scientist (GenAI)

AI Engineer Experience- 3+years
Lead Data Scientist (GenAI) Experience- 7+years
Notice Period- 15 days/30days Max (who serving Notice Period)
Walkin Drive Location- Hyderabad
Date of drive- 24th Aug 2025(Sunday)

Must have Experience:
LLM, Advance RAG, NLP, transformer model, LangChain
Technical Skill:
1. Strong Experience in Data Scientist (GENAI)
2. Proficiency with Generative AI models like GANs, VAEs, and transformers
3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models
4. Strong Python Fast API experience, SDA based implementations for all the APIs
5. Knowledge of Agentic AI concepts and applications

EXL is looking for a Senior Neo4j Developer to join our growing data engineering team!

🧠 Experience Required:
✔️ 10+ years overall in software/data engineering
✔️ 4+ years of hands-on experience with Neo4j
✔️ Strong background in Python and PySpark
✔️ Experience in graph modeling, Cypher queries, and big data pipelines

🌐 Location: Open to all EXL locations [Hybrid]

Join us to build cutting-edge graph-based solutions that solve real-world business problems.

📩 Interested or know someone who might be a great fit? Let’s connect!
Share your resume at Qareena.Kazi@exlservice.com

𝟳 𝗠𝘂𝘀𝘁-𝗛𝗮𝘃𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 𝘁𝗼 𝗟𝗮𝗻𝗱 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱😍

Want to land a career in data analytics? 📊💥

It’s not about stacking degrees anymore—it’s about mastering in-demand skills that make you stand out in a competitive job market🧑‍💻📌

𝐋𝐢𝐧𝐤👇:-

http://pdlink.in/3Uxh5TR

Start small, practice every day, and add these skills to your portfolio✅️

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 👍👍

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

📌SONY is hiring for Machine Learning Role
Experience: 0 - 2 years
Apply here: https://www.linkedin.com/jobs/view/4290651291/

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

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, Descriptive & 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://t.me/datalemur

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🚀🔥 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

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

🚀 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

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

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

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

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

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🚀 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

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]

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

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://t.me/addlist/4q2PYC0pH_VjZDk5

All the best 👍👍