Tabby

Data Analyst

• Configure internal queues in the CRM for distributing tickets to agents.
• Analyze and optimize prioritization logic, SLA paths, and fallback routing.
• Support special scenarios: escalations, VIP cases, language queues, shift-based routing.
• Perform regular audits of rule correctness and their impact on SLA and workload.
• Monitor key metrics: SLA, AHT, backlog, occupancy, shrinkage.
• Detect anomalies in data and investigate root causes of deviations.
• Analyze the impact of queue and process changes on service metrics.
• Prepare regular performance analytics and reports for management.
• Calculate required agent headcount based on forecasts and SLA.
• Model “what-if” scenarios: marketing activities, SLA changes, new processes or products.
• Evaluate schedule effectiveness and recommend optimal resource allocation.
• Build time series forecasts for incoming tickets, chats, and calls.
• Identify seasonal patterns, spikes, and holiday effects.
• Prepare short-term and long-term forecasts (interval, weekly, monthly horizons).
• Update forecasts considering product changes, marketing activity, and process updates.
• Write SQL queries to retrieve data from the analytics database.
• Collect data from multiple sources (CRM, BI systems, queue logs).
• Prepare and clean datasets for forecasting models.

Senior Data Analyst, WFM

Operations

• LLM Serving & Model Management:
• Deep expertise in high-throughput serving using vLLM, NVIDIA TensorRT-LLM, and sglang to minimize latency and maximize hardware efficiency.
• Hands-on experience deploying and optimizing large-scale open-weights models, specifically DeepSeek 3.1/3.2, Qwen, and GPT-OSS variants.
• Advanced optimization and security hardening of Docker specifically for GPU environments.
• Managing model weights and orchestration within Kubernetes (GKE) environments.
• Real-Time Data Engineering & CDC:
• Designing and maintaining high-throughput CDC (Change Data Capture) pipelines using the Apache ecosystem (e.g., Debezium, Kafka) to sync data from Cloud PostgreSQL.
• Deploying and tuning ClickHouse for real-time analytics, ML feature storage, and high-speed logging.
• Orchestrating complex ML data workflows using Airflow (Google Cloud Composer) to ensure data reliability.
• Core Infrastructure & Networking:
• Strong Linux systems expertise including internals, networking, and performance tuning for large-scale distributed systems.
• Experience with Istio service mesh to manage microservices communication and traffic.
• Provisioning and maintaining dedicated GPU nodes (A100/H100/H200/B200), including driver management and OS-level tuning using Ansible.
• Solid Kubernetes expertise: controllers, CRDs, CNI, and Ingress.
• CI/CD & Tooling:
• Implementing pipelines as code within GitLab CI, managing runners, caching, and security scanning.
• Infrastructure as Code with Terraform and Terragrunt.
• Proficiency in Python/Bash for building custom automation and AI Agent tooling.
• Load Testing & Observability:
• Conducting rigorous load testing for GenAI applications, focusing on metrics like TTFT, TPS, and RPS.
• Deploying and managing LiteLLM Gateway for unified API access, load balancing, and cost tracking.
• Experience with Datadog for monitoring GPU utilization, inference health, and log pipelines.
• Soft Skills:
• Strong ownership mindset: balancing speed, reliability, and cost.
• Comfortable working cross-functionally with developers, security, and compliance.
• Excellent sense of responsibility and accountability.
• English B2 or higher.
• Nice to Have:
• Experience with PCI-DSS, SOC2, or regulations compliance environments.
• Our Tech Stack: Linux, Docker, Kubernetes, GCP (GKE, Cloud PostgreSQL), Datadog, GitLab, Apache CDC, ClickHouse, Airflow, Istio, Terraform, Terragrunt, Ansible, vLLM, TensorRT-LLM, sglang, LiteLLM, DeepSeek, Qwen, Go, Python

Senior ML/Data Ops Engineer II

Data Scientist

• Design, develop, and maintain risk models using advanced machine learning techniques, including hybrid and sequential approaches.
• Regularly retrain, monitor, and validate existing models to ensure timely adaptation to changing customer behavior.
• Build and manage scalable data marts in BigQuery to support model development and analytical needs.
• Contribute to development of internal automation tools (e.g., AutoML components, ML workflows).
• Provide data-driven insights through ad-hoc analyses to support product, credit, and operations teams.
• Participate in early research and prototyping of new architectures (Transformers, foundation-style embeddings, multimodal models).

Data Scientist – Risk

• - Design, develop, and maintain risk models using advanced machine learning techniques, including hybrid and sequential approaches.
• - Regularly retrain, monitor, and validate existing models to ensure timely adaptation to changing customer behavior.
• - Build and manage scalable data marts in BigQuery to support model development and analytical needs.
• - Contribute to development of internal automation tools (e.g., AutoML components, ML workflows).
• - Provide data-driven insights through ad-hoc analyses to support product, credit, and operations teams.
• - Participate in early research and prototyping of new architectures (Transformers, foundation-style embeddings, multimodal models).

Data Scientist, Risk

Analyst

• Collection, analysis, clarification, and formalization of requirements;
• Implementation and maintaining technical documentation up to date;
• Participation in the construction of architecture and interaction schemes;
• Identifying affected project teams (for large projects);
• Assistance in developing test cases and A/B experiments;

Senior System Analyst

DevOps Engineer

• Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 15 million users choose Tabby to stay in control of their spending and make the most out of their money.
• **The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.
• **Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region.
• **Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion.**

Senior ServiceDesk Reliability Engineer – SDRE

Backend Engineer

• Development of backend for AI agent platform and microservices around it
• Participate in the architecture setup, in choosing technologies
• Stay up to date with updates and frameworks around AI agent technologies, study and experiment.
• Improve and optimize parts of the platform related to agent creation, quality evaluation, and performance under load.
• Work closely with platform clients, take feedback into account, and help build a user-friendly product.

Senior Python Software Developer

• Develop backend for AI agent platform and microservices around it
• Participate in architecture setup and technology choices
• Stay up to date with updates and frameworks around AI agent technologies, study and experiment
• Improve and optimize parts of the platform related to agent creation, quality evaluation, and performance under load
• Work closely with platform clients, take feedback into account to build a user-friendly product

QA Engineer

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Senior QA Engineer – Full-Stack, Backend, Mobile

• Analyze customers and merchants financial data to derive actionable insights
• Develop reports and dashboards to support various reporting lines (external & internal reporting)
• Ensure the accuracy and consistency of data across multiple sources for reconciliation; identifying and resolving discrepancies, ensuring the integrity of data, and providing reliable insights to support decision-making processes
• Investigate and analyze the underlying causes of data discrepancies, collaborating with relevant stakeholders to resolve issues and prevent future occurrences.
• Engage in risk/finance analytics and ad-hoc inquiries
• Participate in designing and enhancing various risk/finance processes
• Develop and maintain ECL calculations models including but not limited to: PD, LGD, EAD under IFRS-9 guidelines
• Perform initial validation of risk models to ensure compliance with IFRS 9 standards.
• Collaborate with cross-functional teams to provide data-driven insights for product launches and operational improvements.
• Optimize existing processes through automation and policy development.

Senior Data Analyst, WFM

Senior ML/Data Ops Engineer II

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Data Scientist – Risk

Data Scientist – Risk

Senior System Analyst

Senior ServiceDesk Reliability Engineer – SDRE

Data Scientist, Risk

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Senior Python Software Developer

Senior Python Software Developer

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