Wallet in Telegram is a digital asset solution natively embedded into Telegram’s interface. Backed by The Open Platform, Wallet in Telegram gained 100M+ user accounts in 2024, and aims to make its solution available to all 1BN+ of Telegram’s users. Wallet in Telegram offers a dual-wallet experience with Crypto Wallet (a multi-chain wallet for trading and sending crypto to contacts) and TON Wallet (a self-custodial wallet with access to the TON ecosystem of dApps and tokens).

As a Data Analyst in Support Operations, you will work at the intersection of data, product, and support operations. Your focus will be to understand why users contact support, where operational bottlenecks appear, and how support processes can be improved at scale.

This role is not limited to building dashboards. We are looking for someone who enjoys digging into operational workflows, investigating root causes behind SLA, backlog, CSAT, contact rate, and workload changes, and turning messy support data into clear insights and practical recommendations.

Key challenges:

• Working with large volumes of operational support data: tickets, chats, queues, tags, agent activity, SLA events, CSAT surveys, backlog, escalations, and automation flows.

• Identifying bottlenecks in support workflows and explaining what drives changes in SLA, FRT, ART, AHT, backlog, CSAT, and contact rate.

• Connecting support data with product and process context: KYC, payments, transactions, onboarding, product releases, incidents, and user communications.

• Building scalable dashboards, automated reporting, and a reliable single source of truth for support metrics.

• Enabling support operations teams with self-service analytics, reducing routine data requests, and creating more space for deeper insights and high-impact recommendations.

• Turning analysis into practical recommendations for process optimization, automation, self-service, staffing, and product improvements.

Responsibilities:

• Own and develop the customer support metrics framework: SLA, FRT, ART, AHT, CSAT, backlog, contact rate, reopen rate, escalation rate, occupancy/utilization, and other operational metrics.

• Build, maintain, and optimize dashboards and automated reporting for support leadership, team leads, and cross-functional stakeholders.

• Conduct regular and ad-hoc analyses of support operations, including ticket volume, workload, queue performance, backlog growth, SLA breaches, and CSAT changes.

• Investigate root causes behind spikes in support contacts, SLA degradation, CSAT drops, backlog growth, or increased resolution time.

• Identify bottlenecks in ticket and chat workflows, including routing, prioritization, escalation, handoffs, agent workload, and automation gaps.

• Analyze support contact drivers and connect them with product issues, user journeys, KYC/payment flows, incidents, product releases, and communication gaps.

• Translate analytical findings into practical recommendations for process improvements, automation, self-service, and product fixes.

• Monitor data quality, tagging consistency, and metric calculation accuracy.

Requirements:

• 3+ years of experience as a Data Analyst, Operations Analyst, Product Analyst, or similar role.

• Hands-on experience with customer support, operations, marketplace, fintech, logistics, trust & safety, risk, compliance, or another high-volume operational domain.

• Strong understanding of support or operational metrics: SLA, FRT, ART, AHT, CSAT, backlog, contact rate, occupancy/utilization, reopen rate, escalation rate, or similar.

• Strong SQL skills: complex queries, joins, aggregations, window functions, data validation, and building reusable datasets.

• Experience with BI tools such as Tableau, Power BI, Looker, DataLens, Superset, or similar.

• Ability to work with messy operational data, inconsistent tags, changing processes, and ambiguous business questions.

• Strong analytical thinking.

• Interest in operational processes and willingness to understand how support teams actually work: queues, workflows, routing, escalations, staffing, automation, and quality control.

• Ability to communicate insights clearly to non-technical stakeholders and influence operational decisions.

• Basic understanding of product analytics is a plus.

• Python experience is a plus.

Why it is a fantastic opportunity:

• Our business is growing at an exponential scale.

• Non-bureaucratic management that focuses on results.

• Regular performance reviews to assess your progress.

• Remote setup with access to our hubs in Dubai, Yerevan, London and Belgrade.

• Compensation for medical expenses.

• Provision of necessary equipment.

• Employees get access to the most advanced AI models via mira.tg.

• 20 working days of paid vacation annually.

• 11 days off per year.

• 14 days of paid sick leave to support your health and recovery when needed.

• Access to internal conferences, English courses and corporate events.