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REQUIREMENT_ID_1840 • 3-DAY_ACTIVE_POLICY JD

Get Unstoppable on LinkedIn

Company
Company Featured Tech Partner
Type
Opportunity Type Internship
Salary
Stipend / Salary 10-20 LPA
Location
Location Online
Posted Date
Posted Date Today
Apply on Official Website ↗
Analytical thinking problem solving time management content creation professional networking LinkedIn proficiency written communication creativity attention to detail
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Aptitude Practice Questions Open Resource ↗
Curated quantitative and logical reasoning problems to sharpen the analytical speed needed for the LinkedIn Zip puzzles.
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Company Interview Preparation Resources Open Resource ↗
Comprehensive guides on interview formats and common recruiter expectations, useful for crafting compelling LinkedIn posts and networking.
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Comprehensive Study Guides Open Resource ↗
Detailed notes and strategies for various aptitude and reasoning topics, helping participants improve their puzzle‑solving efficiency.
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Algorithm and Data Structure Problem Sets Open Resource ↗
Practice problems that enhance logical thinking and problem‑decomposition skills, directly applicable to daily LinkedIn Zip challenges.

Open to all students (undergraduate, postgraduate) and working professionals across any discipline who have an active LinkedIn account. Participants must create a verified LinkedIn profile, have a minimum of 30 connections, and opt‑in to receive recruiter calls. No academic percentage or backlog restrictions are mentioned, but accurate education and professional details must be provided during registration. Only verified profiles will be considered for prize eligibility.

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Round 1: LinkedIn Zip Puzzle Challenge
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Round 2: Content Creation Challenge (5 LinkedIn posts)
3
Overall Leaderboard Evaluation (combined scores)
4
Top performers receive cash prizes, editorial features, and Next Gen Club invitations
Unstop.com, formerly known as Internshala’s competition platform, is a leading Indian career‑building ecosystem that connects millions of students and fresh graduates with internships, entry‑level jobs, and skill‑based challenges. The platform prides itself on fostering a culture of continuous learning, real‑world problem solving, and community engagement. By leveraging partnerships with global brands and professional networks such as LinkedIn, Unstop creates immersive experiences that help participants sharpen their professional presence, showcase their talents, and earn tangible rewards. The company’s mission is to eliminate the "lurker" mindset and empower every learner to become a proactive contributor in the digital workplace. The "Get Unstoppable on LinkedIn" competition is a flagship initiative designed to blend gamified problem‑solving with content creation on the world’s largest professional network. Over a span of six weeks, participants will engage in two core challenges: the LinkedIn Zip puzzle series and a series of prompt‑driven LinkedIn posts. The competition not only tests analytical speed and creativity but also encourages participants to build a robust LinkedIn profile, expand their network, and develop a personal brand that stands out to recruiters. Winners receive cash prizes, public recognition on LinkedIn leaderboards, editorial features, and exclusive invitations to the LinkedIn Next Gen Club, along with potential pre‑placement interview (PPI) opportunities with Unstop’s partner companies. Key responsibilities for participants include: 1. Create and verify a complete LinkedIn profile with at least 30 connections. 2. Play the LinkedIn Zip puzzle at least ten times, solving daily challenges released at 12:30 PM IST. 3. Maintain an average solving time that places them in the top tier of the leaderboard. 4. Craft five high‑impact LinkedIn posts responding to official prompts, using the required hashtags (#MyLinkedInEra, #BeUnstoppable). 5. Submit accurate post URLs on the Unstop portal before the stipulated deadlines. 6. Engage with the competition community by following the official LinkedIn page for leaderboard updates. 7. Adhere to all eligibility criteria, including profile verification and accurate personal information. 8. Demonstrate professionalism and originality in all content to avoid disqualification. The tech stack for this challenge is primarily the LinkedIn platform itself, supplemented by Unstop’s competition portal. Participants will use LinkedIn’s publishing tools, analytics, and networking features, while Unstop provides a secure registration system, real‑time leaderboards, and automated verification processes. Growth paths emerging from this competition include enhanced visibility to recruiters, potential internships or entry‑level roles with Unstop’s partner ecosystem, and a stronger personal brand that can accelerate career progression. Why join? Apart from the attractive cash rewards, participants gain hands‑on experience in personal branding, content strategy, and rapid problem solving—skills highly valued by modern employers. The competition also offers a unique chance to be featured in LinkedIn editorial pieces, join an exclusive professional community, and receive mentorship opportunities. For students and early‑career professionals eager to transition from passive observers to active contributors, "Get Unstoppable on LinkedIn" provides a structured, rewarding pathway to showcase talent, expand networks, and kick‑start a successful career.

Featured Tech Partner — AI & Machine Learning Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE 🎯
Featured Tech Partner Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Featured Tech Partner and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Analytical thinking, problem solving, time management, content creation, professional networking, LinkedIn proficiency, written communication, creativity, attention to detail) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Featured Tech Partner Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the bias-variance tradeoff and how do you prevent overfitting? Answer ▼
Model Answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer ▼
Model Answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer ▼
Model Answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer ▼
Model Answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Why do you want to join Featured Tech Partner as a Get Unstoppable on LinkedIn?
Preparation Tip: Highlight Featured Tech Partner's market reputation, recent tech innovations, and how your skills in Analytical thinking directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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