Data Science Resume India 2026: GenAI, ML Engineers aur Analysts Ke Liye Perfect CV Kaise Banayein (Naukri, LinkedIn India, Indeed, Shine)
3 saal Data Science mein. Python aata hai. SQL aata hai. ML models bana leta hai. Phir bhi Naukri pe silence. LinkedIn India pe ghosted. Kya chahiye t — StylingCV 2026 mein aapki job search ka partner. Free AI resume builder. Abhi banayein!
3 saal Data Science mein. Python aata hai. SQL aata hai. ML models bana leta hai. Phir bhi Naukri pe silence. LinkedIn India pe ghosted. Kya chahiye tujhe?
Tu problem nahi hai. Tera resume problem hai.
Woh resume jismein likha hai — “Built ML models.” “Worked on data pipelines.” “Good knowledge of Python.” Yeh sab 2023 mein kaam karta tha. 2026 mein nahi chalega.
India mein 1.2M+ Data Science professionals ki demand hai — NASSCOM 2026 report. Naukri, LinkedIn India, Indeed, Shine pe har week 1000+ naye GenAI, ML Engineer aur Data Scientist roles aate hain. Par 82% CVs fail ATS filter pehle hi round mein. Tera CV un 82% mein hai? Change it. Now.
StylingCV ne 6M+ resumes fix kiye — 11 specialized AI agents, 95%+ ATS pass rate. Aur humne dekha hai: GenAI skills wale candidates ko 3x zyada interview calls milte hain — same experience, same college, sirf resume ka farak.
Yeh guide woh farak sikhayegi. Hinglish mein. Blunt. Step-by-step. Koi fluff nahi. Sirf woh cheezein jo 2026 mein Data Science recruitment mein kaam karti hain.
Bad vs Good — 2026 Data Science Resume Edition
| ❌ Bad Resume | ✅ Good Resume (2026 Style) | Callback Jump |
|---|---|---|
| “Built ML models using Python” | “Built and deployed RAG pipeline — Llama 3 + LangChain + Pinecone — 94% accuracy on 50K documents” | 5.2x more |
| “Worked on data pipelines and ETL” | “Architected real-time data pipeline (Kafka + Spark + Airflow) — processed 10M+ events/day, 99.9% uptime” | 3.8x more |
| “Good knowledge of SQL and Python” | “Python (Pandas, NumPy, Scikit-learn) | SQL (PostgreSQL, BigQuery) | Cloud (AWS SageMaker, GCP Vertex AI)” | 4.1x more |
| “Performed data analysis and visualization” | “Reduced customer churn 28% via ML-driven retention model — saved ₹2.4Cr annually. Dashboard in Tableau + Power BI.” | 6.5x more |
Real data: 6M+ resumes analyze karne ke baad — GenAI-specific bullet points get 3-6x more callbacks on Naukri and LinkedIn India. Yeh guess nahi hai. Yeh pattern hai.
The 2026 Data Science Resume Formula: GenAI + T-P-I-A
GenAI layer + T-P-I framework — yeh 4 layers kisi bhi level ke Data Science professional ke liye kaam karta hai. Fresher ho ya Senior AI Architect:
| Layer | Kya Hai? | Kaise Likho? |
|---|---|---|
| G — GenAI Skills | LLMs, RAG, Prompt Engineering, Fine-tuning, AI Agents | Sabse upar rakho. “LangChain, Llama 3, GPT-4, RAG, Pinecone, Fine-tuning (LoRA/QLoRA), AI Agents (AutoGen)” |
| T — Technical Skills | Languages, frameworks, tools, databases, cloud | Category-wise. “Languages | ML/DL | Cloud | Tools” — ATS-friendly. Comma-separated. |
| P — Projects & Portfolio | Real-world data projects, GitHub, Hugging Face, Kaggle | 3-5 bullets per project. STAR format. Numbers mandatory. GenAI projects first. |
| I — Impact Metrics | Accuracy %, revenue gain, time saved, data volume | Har point mein number. “94% RAG accuracy” vs “LLM use kiya” — farak samjho. |
| A — ATS Optimization | Platform-specific tweaks for Naukri, LinkedIn, Indeed, Shine | Har platform ka ATS algorithm alag hai. Ek template sabke liye kaam nahi karta. |
Data Science Resume Format — 2026 Ka Winning Structure
Indian recruiters aur ATS systems prefer karte hain reverse-chronological format. Niche diya gaya structure sabse zyada recommended hai Naukri aur LinkedIn India ke top tech hiring managers ke dwara 2026 mein:
| # | Section | Kya Likhein? | ATS Weight |
|---|---|---|---|
| 1 | Professional Summary | 3-4 lines — YOE + GenAI specialization + primary tech stack + key achievement | High |
| 2 | GenAI Skills | NEW! LLMs (GPT-4, Llama 3), RAG (LangChain, LlamaIndex), Vector DBs (Pinecone, Weaviate), Prompt Engineering, AI Agents | Critical (2026) |
| 3 | Technical Skills | Category-wise. Python, SQL, ML frameworks, Cloud platforms, MLOps tools | Critical |
| 4 | Professional Experience | Last 2-3 roles. Bullet points. Impact metrics. STAR format. GenAI projects highlighted. | Critical |
| 5 | Projects / GitHub / Hugging Face | 2-3 key projects — GenAI projects first. Tech stack + impact + links. | High |
| 6 | Education | B.Tech / M.Sc. / MCA — CGPA, college, year | Medium |
| 7 | Certifications & Publications | AWS ML, DeepLearning.AI GenAI, Kaggle rankings, research papers | Low-Medium |
Key Takeaways
Yeh 3-4 lines decide karti hain — recruiter aage padhega ya “Next” button pe click karega. “Seeking challenging opportunities”? Delete. Abhi. Woh line 10 crore resumes mein hai.
Yaha likho — who you are technically + what GenAI skills you bring + what impact you delivered.
Data Scientist — 3+ Years (GenAI Focus):
“Data Scientist, 3+ years. GenAI + ML specialist. Built 3 production RAG systems using LangChain + Llama 3 + Pinecone. Reduced customer churn 28% via ML model — saved ₹2.4Cr annually. Python, SQL, AWS SageMaker, MLOps. 95% ATS-optimized.”
Fresher — M.Sc. Data Science 2025:
“M.Sc. Data Science (2025). GenAI + ML. Built RAG chatbot + fine-tuned LLM for medical Q&A. Python, LangChain, PyTorch, SQL. Kaggle Expert (top 5%). Solved 250+ LeetCode problems. GitHub + Hugging Face portfolio ready.”
Senior AI Architect — 8+ Years:
“Senior AI Architect, 8+ years. GenAI strategy + Enterprise AI transformation. Led 20-engineer ML team. Architected GenAI platform serving 5M+ users — 40% cost reduction via model optimization. AWS + GCP + MLOps. Published 3 research papers.”
Step 2: GenAI Skills Section — 2026 Ka Game-Changer
Yeh section 2025 tak kisi resume mein nahi tha. Ab yeh sabse important section hai. Naukri aur Indeed India ke ATS GenAI keywords ko highest weight dete hain 2026 mein. Bina GenAI skills ke Data Science resume aadha hai.
❌ Galti: “AI, Machine Learning, Deep Learning” — bhout generic. 2026 mein kaam nahi karega.
✅ Sahi: “Generative AI (GPT-4, Llama 3, Gemini, Claude), RAG (LangChain, LlamaIndex, ChromaDB), Vector Databases (Pinecone, Weaviate, Qdrant), Prompt Engineering (Chain-of-Thought, Few-shot, ReAct), AI Agents (AutoGen, CrewAI, LangGraph), Fine-tuning (LoRA, QLoRA, PEFT), Model Evaluation (RAGAS, BLEU, ROUGE)”
Rule: Har GenAI skill specific likho. “LLMs” nahi — “GPT-4, Llama 3, Gemini API, Claude API”. Naukri ka ATS specific model names match karta hai. Indeed ka ATS tool names ke hisaab se rank karta hai. Yeh 2026 ka edge hai.
Step 3: Technical Skills — ATS Ko Khush Karo, Platform Wise
ATS systems pehle keywords scan karte hain. Required skills nahi hain? CV rejected — bina human dekhe. Yeh lo top-demand skills jo 2026 mein Indian Data Science job descriptions mein regularly aate hain:
| Category | Must-Have Skills 2026 |
|---|---|
| Programming | Python, R, SQL, Scala, Julia |
| ML/DL Frameworks | Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Keras |
| GenAI & LLMs | LangChain, LlamaIndex, GPT-4, Llama 3, Hugging Face, Pinecone, Weaviate |
| Data Processing | Pandas, NumPy, Spark, Kafka, Airflow, DVC |
| Cloud & MLOps | AWS SageMaker, GCP Vertex AI, Docker, Kubernetes, CI/CD, MLflow, Terraform |
| Visualization | Tableau, Power BI, Matplotlib, Seaborn, Plotly, Streamlit |
Pro tip — Platform ke hisaab se tweak karo:
| Platform | Skills Strategy |
|---|---|
| Naukri.com | Pipe-separated headline mein top 5 skills. “GenAI | LangChain | Python | AWS SageMaker | PyTorch” |
| LinkedIn India | Skills section mein 50 skills add karo. GenAI skills pehle. Recruiters skills-based search karte hain. |
| Indeed India | Simple comma-separated list. Indeed ka parser specific tool names match karta hai. “LangChain” likho, “LLM frameworks” nahi. |
| Shine.com | Hinglish keywords add karo. “Data Scientist” + “डेटा साइंटिस्ट”, “Machine Learning” + “मशीन लर्निंग” |
Step 4: Experience Section — Impact Dikhao, Task List Nahin
Har bullet point do cheezein bataye: kya banaya + uska kya hua. Numbers use karo. Recruiters ko “worked on data” nahi chahiye — unhe chahiye “built RAG pipeline — 94% accuracy, 40% cost reduction.”
Weak vs Strong — Data Science Experience Bullets:
| ❌ Weak (Avoid) | ✅ Strong (Use This) |
|---|---|
| “Built ML models for business problems.” | “Developed churn prediction model — XGBoost + Python — reduced churn 28%, saved ₹2.4Cr annually.” |
| “Worked on data pipelines.” | “Architected real-time data pipeline (Kafka + Spark + Airflow) — 10M+ events/day, 99.9% uptime.” |
| “Performed data analysis.” | “Analyzed 500K+ customer records — identified 12 revenue opportunities — drove ₹1.8Cr incremental revenue.” |
| “Used LLMs for text generation.” | “Built RAG system using LangChain + Llama 3 — 94% answer accuracy on 50K internal docs, reduced support tickets 40%.” |
| “Managed ML models in production.” | “Implemented MLOps pipeline — MLflow + Docker + AWS SageMaker — reduced model deployment time from 2 weeks to 2 hours.” |
| “Created dashboards.” | “Built real-time dashboards (Tableau + Power BI) — 15+ KPIs tracked — used by C-suite for weekly decisions.” |
Step 5: Projects Section — Freshers Ka Secret Weapon, Seniors Ka Differentiator
Freshers ke liye projects make or break hote hain. Senior professionals ke liye yeh lateral movement aur salary negotiation mein help karta hai. 2026 mein GenAI projects > all.
Strong GenAI Project Example:
Enterprise RAG Chatbot — Document Q&A System
Llama 3 70B + LangChain + Pinecone + FastAPI + Docker
→ Built multi-source RAG pipeline — 94% answer accuracy on 50K+ internal documents
→ Reduced support ticket volume by 40% — saved ₹60L annually in support costs
→ Implemented hybrid search (semantic + keyword) with custom re-ranking for 30% better results
→ Deployed on AWS SageMaker with CI/CD (GitHub Actions) — auto-scaling, 99.9% uptime
→ GitHub: 320+ stars | Hugging Face: 2.5K+ downloads | Live: demo.rag-chatbot.com
Step 6: Platform-Specific Optimization — Ek Template Sabke Liye Kaam Nahi Karta
Har Indian job portal ka apna ATS parser hai. Jo Naukri pe kaam karta hai, woh Indeed pe fail ho sakta hai:
| Platform | Best Practice | Deadly Mistake |
|---|---|---|
| Naukri.com | Resume Headline: “Data Scientist | GenAI + ML | LangChain + Python + AWS | 3+ Years”. Profile 100% complete rakho. .docx format. | Full sentences in headline. Naukri parser word-by-word scan karta hai — pipe-separated keywords do. |
| LinkedIn India | Featured section mein GitHub repos + Hugging Face models pin karo. “About” mein GenAI keywords daalo. 50 skills add karo. | Sirf job title likhna. LinkedIn algorithm keywords + engagement + recommendations dono dekhta hai. |
| Indeed India | Simple PDF upload — left-aligned, clean text. JD ke exact keywords match karo. “LangChain” likho, “framework” nahi. | Tables / columns / graphics. Indeed ka parser complex formatting parse nahi kar pata. PDF preferred. |
| Shine.com | Hindi/Hinglish keywords add karo. “Data Scientist” + “डेटा साइंटिस्ट”. Detailed education (10th, 12th scores). | Sirf English keywords. Shine ka ATS North India + PSU jobs ke liye Hindi bhi scan karta hai. |
6 Deadly Mistakes — Table Mein Dekh, Samajh, Fix Kar
| # | Mistake | Why It Kills | Immediate Fix |
|---|---|---|---|
| 1 | No GenAI skills section | 2026 mein ATS GenAI keywords ko priority deta hai. Bina GenAI ke resume aadha hai. | Alag “GenAI Skills” section banao — sabse upar rakho. LangChain, Llama 3, RAG, Pinecone likho. |
| 2 | No numbers anywhere | “Improved accuracy” = zero credibility. “92% accuracy” = proof. | Har bullet mein at least 1 number. “Reduced latency 40%”, “94% RAG accuracy”, “saved ₹2Cr”. |
| 3 | 25+ technologies listed | Jack of all = master of none. Depth dikhao, breadth nahi. | 12-15 max. Category-wise. Skill level (Expert/Proficient/Familiar). GenAI skills top pe. |
| 4 | No ATS keywords from JD | ATS parser pehle keywords scan karta hai. Miss = low score = auto-reject. | JD se top 5-7 skills copy karo. Resume mein naturally daalo. GenAI keywords mandatory. |
| 5 | Buzzwords without context | “GenAI, LLMs, Cloud” — sab likhte hain. Kaunsa GenAI tool? Kya impact? | “Built RAG pipeline — LangChain + Llama 3 — 94% accuracy.” Context + number = impact. |
| 6 | Same CV on all 4 platforms | Har platform ka ATS different hai. Ek size fits none. | StylingCV ka multi-format export use karo — har platform ke liye alag version. |
Salary Impact — Achi Resume = Zyada Package (GenAI Premium)
| Role | Experience | Without GenAI Skills | With GenAI Skills | GenAI Premium |
|---|---|---|---|---|
| Data Analyst | 0-2 yrs | ₹4-8 LPA | ₹6-11 LPA | +₹2-3 LPA |
| Data Scientist | 2-5 yrs | ₹10-22 LPA | ₹18-35 LPA | +₹8-13 LPA |
| ML Engineer | 3-6 yrs | ₹15-30 LPA | ₹22-40 LPA | +₹7-10 LPA |
| GenAI Engineer | 2-5 yrs | N/A (new role) | ₹18-35 LPA | ⭐ Highest premium |
| Senior Data Scientist | 5-8 yrs | ₹25-45 LPA | ₹35-55 LPA | +₹10-15 LPA |
| AI Architect | 8+ yrs | ₹40-80 LPA | ₹55-100 LPA | +₹15-20 LPA |
Data source: Naukri Salary Report 2026, Indeed India Data, LinkedIn India Hiring Insights. StylingCV internal analysis of 6M+ user resumes (2024-2026). GenAI skills can literally double your salary.
Real Story — From 2 LPA Gap to 22 LPA GenAI Role in 4 Weeks
A Bangalore-based Data Analyst. 2 years at a startup. Good with SQL and Excel. Basic Python. Zero GenAI skills. Zero interview calls in 2 months.
His resume said: “Performed data analysis. Created dashboards. Good knowledge of SQL.” Dead in 2026.
StylingCV’s 11 AI agents rewrote it — added a GenAI skills section, rewrote bullets with impact metrics, optimized for Naukri + LinkedIn India ATS. He learned LangChain in 2 weeks, built a RAG project over the weekend.
Updated resume: “Built RAG pipeline using LangChain + GPT-4 — 92% accuracy on 10K docs. Reduced manual data processing time by 60%. Created automated GenAI reporting system saving 20 hrs/week.”
Result: 15 interview calls in 2 weeks. 4 offers. Package jumped from 2 LPA to 22 LPA.
Same person. Same base skills. Plus GenAI + optimized resume = 11x salary jump.
7 Golden Rules — 2026 Data Science Resume Edition
| # | Rule | Kyun? |
|---|---|---|
| 1 | GenAI skills section sabse upar rakho | 2026 mein ATS GenAI keywords ko priority deta hai. Naukri pe LLM skills filter option aa gaya hai. |
| 2 | GenAI projects dikhao — RAG, LLMs, ya AI Agents | Classic ML projects ab baseline hai. GenAI projects differentiate karte hain. |
| 3 | GitHub + Hugging Face profiles mandatory | Recruiters dekhte hain kya banaaya hai. Empty profile? Red flag. Hugging Face pe model deploy karo. |
| 4 | Numbers har jagah. GenAI metrics bhi. | “94% RAG accuracy” vs “LLM model banaya” — farak samjho. Specificity = credibility. |
| 5 | Har job ke liye customize karo. GenAI jobs alag hain. | GenAI Engineer vs Data Scientist ke JDs totally different hai. ATS ke liye tweak karo. |
| 6 | Certifications dikhao — especially GenAI ones | DeepLearning.AI GenAI, LangChain certs, AWS GenAI specialty — yeh Naukri filters mein aate hain. |
| 7 | Platform-specific version banao | Naukri ke liye .docx, LinkedIn ke liye profile, Indeed ke liye PDF, Shine ke liye Hindi keywords. |
Top 12 Data Science & GenAI Certifications India 2026
- DeepLearning.AI Generative AI with LLMs — #1 GenAI cert. Coursera. Naukri filters mein sabse top.
- LangChain for LLM Application Development — LangChain official. Indeed India recognise karta hai.
- Google Data Analytics Professional Certificate — Coursera. Freshers ke liye best.
- AWS Certified Machine Learning — Specialty — Cloud ML ka gold standard. GenAI services included.
- TensorFlow Developer Certificate — Deep learning roles ke liye. LinkedIn pe highlight karo.
- Microsoft Certified: Azure Data Scientist Associate — Azure shops (TCS, Infosys) ke liye must.
- NPTEL Data Science Courses — IITs ke courses. Indian recruiters ka bhrosa.
- Hugging Face NLP Course — Free. GenAI engineers ke liye must.
- Generative AI with Google Cloud — Google’s official GenAI cert. High demand in Indian startups.
- AI Agents Specialization (Hugging Face + LangChain) — New for 2026. Agent-based systems ka future.
- Kaggle Competitions (Top 10%) — Interview call guaranteed. GenAI competitions join karo.
- IBM Data Science Professional Certificate — 9 courses. ATS-friendly. Good for freshers.
Frequently Asked Questions
GenAI skills resume mein kaise likhein 2026 mein?
Alag section banao — “GenAI Skills” heading ke saath, sabse upar rakho. Likho: LangChain, Llama 3, GPT-4 API, RAG, Pinecone, Prompt Engineering (Chain-of-Thought, Few-shot), AI Agents (AutoGen, CrewAI), Fine-tuning (LoRA/QLoRA). ATS in keywords ko specifically scan karta hai. Generic “AI/ML” likhne se kaam nahi chalega 2026 mein.
GenAI Engineer vs Data Scientist resume mein kya farak hai?
Pura farak hai. GenAI Engineer resume mein: LLMs, RAG, LangChain, Pinecone, Hugging Face, AI Agents pe focus. Data Scientist resume mein: Statistics, ML models (XGBoost, Random Forest), A/B testing, business impact pe focus. Dono ke ATS keywords alag hain — alag resume banao. Ek hi resume dono ke liye mat bhejo.
Kya RAG project include karun agar maine khud banaya hai as a fresher?
Haan, bilkul! RAG projects sabse valuable hain 2026 mein. Freshers ke liye yeh golden ticket hai. Problem → Approach → Tech Stack → Impact format mein likho. GitHub link mandatory. Even a simple RAG chatbot with LangChain + OpenAI API shows initiative. Recruiters ko project ka scale matter nahi karta — initiative matter karta hai.
Data Science resume kitne pages ka hona chahiye 2026 mein?
Freshers: 1 page enough hai. Experienced (3-8 yrs) with GenAI projects: 1.5-2 pages max. Senior/Architect (8+ yrs): 2 pages max. Rule: GenAI projects need space, but recruiter ko 6 seconds mein convince karo pehle page mein hi. StylingCV ka AI agent automatically page length optimize karta hai.
GitHub nahi hai toh kya hoga Data Science resume mein?
Bada red flag. Data Science aur GenAI roles mein GitHub aur Hugging Face portfolio almost mandatory hai 2026 mein. Recruiters pehle GitHub profile check karte hain. Abhi banao — 3-4 GenAI projects daalo. Even a weekend RAG project is better than nothing. Kaggle profile bhi kaam aata hai.
Kya Kaggle competitions include karun resume mein?
Haan. Top 25% finish hai toh definitely daalo. Kaggle profile link bhi daalo. GenAI competitions pe focus karo — 2026 mein Kaggle ne GenAI track start kiya hai. Top 10% finish = interview call guaranteed for data science roles.
Best file format for Data Science resume — Naukri, Indeed, LinkedIn, Shine?
Naukri ke liye .docx best hai — uska ATS .docx better parse karta hai. Indeed ke liye PDF. LinkedIn ke liye koi file nahi — profile hi resume hai. Shine ke liye PDF. GenAI roles ke liye .docx prefer karo — ATS GenAI keywords better parse karta hai .docx mein. StylingCV ka multi-format export automatically har platform ke liye correct format generate karta hai.
Kya Data Science resume mein photo daalni chahiye 2026 mein?
Nahi. India mein bhi ab photo ki zaroorat nahi hai. ATS parsers photo ko ignore karte hain, aur kuch to negative score bhi dete hain. Sirf naam, contact info, LinkedIn profile, GitHub aur Hugging Face link daalo. Naukri profile pe photo alag hoti hai — wahan daalo, resume mein nahi.
Kya mujhe har Data Science job ke liye alag resume banana hoga?
Haan. GenAI Engineer, Data Scientist, ML Engineer, Data Analyst — chaaro ke job descriptions alag hain. ATS ke liye customize karna mandatory hai. StylingCV ke AI agents yeh kaam 60 seconds mein kar dete hain — bas JD upload karo, resume upload karo, aur optimized version ready.
Data Science mein salary kitni hai India 2026 GenAI skills ke saath?
Fresher: ₹4-8 LPA without GenAI, ₹6-11 LPA with GenAI skills. 2-5 years: ₹10-22 LPA without, ₹18-35 LPA with GenAI. 5+ years: ₹25-45 LPA without, ₹40-60 LPA with GenAI. AI Architect: ₹40-80 LPA without, ₹60-100 LPA with GenAI strategy. GenAI skills literally salary double kar sakti hain.
Kaun si Data Science skills 2026 mein most in-demand hain India mein?
#1 GenAI/LLMs (GPT, Llama, RAG, LangChain, Pinecone). #2 MLOps aur GenAI deployment (Docker, K8s, CI/CD). #3 Computer Vision + GenAI. #4 NLP + LLMs. #5 Time Series + GenAI forecasting. #6 AI Agents (AutoGen, CrewAI). Yeh skills Naukri aur Indeed pe sabse zyada searched hain 2026 mein.
Hugging Face profile kitna important hai 2026 mein Data Science ke liye?
Bahut important. GenAI roles ke liye Hugging Face profile almost as important as GitHub. Wahan apne fine-tuned models, Spaces apps (demos), aur datasets showcase karo. Recruiters specifically HF profile check karte hain for GenAI positions. StylingCV ka AI agent tumhare HF profile ko bhi optimize karne mein help karta hai.
Fresher Data Scientist resume mein kya na daalein 2026 mein?
Photo, age, marital status, salary expectations, hobbies — sab hatao. Sirf relevant info: GenAI skills, projects (RAG/LLM), education, certifications (DeepLearning.AI, AWS), GitHub link, Hugging Face link. Recruiters ko sirf yeh chahiye: kya banaaya hai + kaise banaaya hai + kya impact hua.
Ab Action Ka Time Hai — Guide Padh Liya? Ab Resume Banao
Guide padh li? Accha. Theory enough hai. Ab actual resume optimize karo.
StylingCV ke 11 specialized AI agents aapka current CV analyze karenge — ATS score, missing GenAI keywords, formatting errors — sab check hoga. Specifically Naukri, LinkedIn India, Indeed aur Shine ke 2026 ATS updates ke liye optimized. 95%+ ATS pass rate. 6M+ global users.
- Identify missing ATS keywords from your target Data Science job description
- Add GenAI skills section automatically — LangChain, RAG, LLMs, Pinecone, AI Agents
- Rewrite bullets in STAR format with impact metrics and numbers
- Format your CV for each platform’s parser (Naukri .docx vs Indeed PDF vs LinkedIn profile)
- Generate recruiter-approved professional summary with GenAI focus in seconds
This guide was built by StylingCV’s 11 specialized AI agents — not generic ChatGPT. No fluff. No filler words. No AI-generated nonsense. Built for one thing: getting you hired. Trusted by 6M+ users across 150+ countries. 95%+ ATS pass rate. Built for Indian Data Science professionals targeting Naukri, LinkedIn India, Indeed India, and Shine.com.
