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REQUIREMENT_ID_230 β€’ 3-DAY_ACTIVE_POLICY

Insurance Advisory - (Telugu, English)

Company
Company Ditto
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary Not disclosed
Location
Location Remote
Posted Date
Posted Date Today
Great communication skills empathy detail orientation basic tech comfort English fluency Telugu fluency
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Aptitude and Reasoning Practice Open Resource β†—
Helps sharpen analytical thinking and problem‑solving skills for the assessment round.
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Interview Preparation Guide Open Resource β†—
Provides insights into common interview questions and effective response strategies.
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Career Development Resources Open Resource β†—
Offers tips on building a career in advisory and customer service roles.

Bachelor’s degree in any discipline, open to freshers. Fluency in English required; Telugu fluency is a must for this role. Basic computer literacy and familiarity with CRM tools are preferred.

1
Round 1: HR Introductory Call
2
Round 2: Assessment Round
3
Round 3: Task Round
4
Final Managerial Round
Ditto is a fast‑growing fintech startup that has redefined how Indians buy insurance. Backed by Zerodha and part of the Finshots family, Ditto has already helped thousands of customers make informed insurance decisions with clarity and ease. With over 10,000 glowing Google reviews, the company has proven that a customer‑centric, conversational approach can transform a traditionally dry industry. The Insurance Advisory role is designed for freshers who are fluent in Telugu and English. You will be the first point of contact for customers who book appointments or reach out via chat. The job is split into two distinct paths: Team Falcon (call‑first, deep conversation) and Team Bliss (chat‑first, quick and crisp). Depending on your strengths, you can choose the path that best suits you. Key responsibilities include: 1. Engaging with customers through calls or WhatsApp to understand their insurance needs. 2. Explaining product trade‑offs in simple, jargon‑free language. 3. Recommending suitable plans based on individual risk profiles. 4. Guiding customers through the plan selection and purchase process. 5. Maintaining accurate records in the CRM and ensuring follow‑up. 6. Handling post‑sale queries and providing ongoing support. 7. Collaborating with the underwriting team to resolve policy issues. 8. Contributing to knowledge base articles and FAQs. 9. Meeting weekly targets for customer satisfaction and sales. 10. Continuously learning about new products and market trends. Tech stack: Basic CRM tools, WhatsApp Business API, Microsoft Office, and the company’s proprietary advisory platform. Training is provided from scratch, so no prior insurance experience is required. Growth path: After the initial training, successful advisors can progress to senior advisory roles, team lead positions, or even product specialist tracks. Ditto also offers cross‑functional learning opportunities in marketing, data analytics, and product development. Why join Ditto? The company offers a flexible work environment (remote or hybrid), health and term insurance, wellness benefits, menstrual leave, and regular off‑sites and team events. The culture is collaborative, supportive, and focused on ethical selling and customer education. Overall, this role is ideal for communicative, empathetic, and detail‑oriented freshers who want to build a career in the growing insurance tech space.

Ditto β€” AI & Machine Learning Interview Guide

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

APTITUDE & LOGIC πŸ“–
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 β†—
COMPANY GUIDE 🎯
Ditto Interview Preparation Corner

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

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource β†—
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 (Great communication skills, empathy, detail orientation, basic tech comfort, English fluency, Telugu fluency) & 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
Ditto 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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 Ditto as a Insurance Advisory - (Telugu, English)?
Preparation Tip: Highlight Ditto's market reputation, recent tech innovations, and how your skills in Great communication skills 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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