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Fresher Jobs in India

424 active opportunities · Updated October 2026

Explore current job opportunities across India. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Noida, Uttar Pradesh, India
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Job Title: Client Onboarding & Product Specialist Company: Paytm Location: Noida Department: Business / Customer Success / Product Role Overview We are looking for a proactive and customer-focused professional to manage the onboarding and adoption journey of new clients at Paytm. The role involves conducting product demos, guiding clients through setup and integrations, resolving onboarding challenges, and ensuring smooth adoption of Paytm’s solutions. The ideal candidate should have strong communication skills, a problem-solving mindset, and the ability to work closely with Sales, Support, and Product teams. Key Responsibilities Lead new clients through a smooth and structured onboarding process, ensuring successful product setup and activation. ● Conduct product demos, product tours, and personalized training sessions to help clients understand and effectively use Paytm’s solutions. ● Guide clients through WhatsApp Marketing integrations, campaign setup, and relevant product functionalities. ● Act as the primary point of contact during onboarding, addressing setup-related queries and troubleshooting issues to ensure a seamless experience. ● Monitor client adoption and proactively identify opportunities to improve product usage and engagement. ● Simplify complex product or technical processes and help clients move from initial onboarding challenges to confident product usage. ● Collaborate with Sales, Customer Support, and Product teams to resolve client issues and share actionable customer feedback. ● Track onboarding progress, client requirements, and issue resolution while ensuring adherence to defined SLAs. ● Monitor campaign performance and support clients in optimizing their multi-channel campaigns. ● Identify recurring client challenges and work with internal teams to improve processes, product experience, and onboarding journeys. ● Maintain accurate records of client interactions, onboarding status, feedback, and resolutions. Key Skills ●

BA
📍 Bengaluru, KARNATAKA, India· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Bolna Bolna is a YC-backed voice AI orchestration platform built for the Indian market—powering multilingual, vernacular voice agents across Hindi, Hinglish, Tamil, and 10+ languages at sub-500ms latency across collections, recruitment, sales, and e-commerce use cases. We are an orchestration layer, not a model company: our moat is outcome-labelled vernacular data, rigorous evaluation infrastructure, and a growing taxonomy of how Indian enterprise voice AI fails in production. Why This Role Exists Product decisions at Bolna increasingly hinge on rigorous, code-mixed-aware data analysis—and not just one kind. On one side, there is model and evaluation rigor: LLM benchmarking for post-call intelligence, ASR/WER evaluation, inter-rater reliability on human-labelled calls, and routing and latency economics. On the other, there is product and growth insight: understanding where self-serve users drop off in their journey, what patterns emerge across lakhs of monthly calls, and which use cases and configurations are actually working. Both currently sit with the Head of Product alongside strategy and roadmap ownership. We need a dedicated analyst to own the execution and recurring cadence across both-freeing product leadership to act on findings rather than produce them. What You’ll Do Model and Evaluation Analysis LLM and model benchmarking: Run structured comparisons across model providers such as Sarvam, DeepSeek, Gemini, and Claude variants for tasks including post-call extraction and LLM-as-judge scoring. Evaluate cost, accuracy, fill rate, and TTR, with particular attention to Hinglish and code-mixed content. Evaluation infrastructure: Build and maintain LLM-as-judge pipelines using tools such as DeepEval, design and track evaluation metrics, and run inter-rater reliability analysis such as Krippendorff’s alpha across human call reviewers. Golden dataset creation: Support the construction of golden datasets for ASR and transcript labelling, including flagging co

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