MultiBank Group

• Respond to client queries across live chat, email, and phone promptly and professionally. • Provide support to Chinese-speaking clients during Canada coverage hours. • Deliver high-quality support during evening shift operations, ensuring service-level agreements and response-time targets are met. • Support clients through account opening, verification, funding, and withdrawal processes. • Help clients navigate MT4, MT5, and the MultiBank-Plus platform. • Escalate complex or sensitive cases to the relevant internal team and follow through to resolution. • Keep accurate records of client interactions and contribute to knowledge-base improvements. • Follow all compliance, KYC, and data-protection requirements.

• Identify, approach and sign new Introducing Brokers, affiliates and partners across the assigned territory. • Onboard partners and equip them with the tools, materials and commercial terms to perform. • Manage and grow an existing portfolio of IB relationships, increasing the trading volume they generate. • Act as the main commercial contact for partners, resolving issues and identifying growth opportunities. • Track partner performance and report on pipeline, activations and volume. • Operate within the Group's regulatory and compliance framework for the relevant jurisdictions.

• Respond to client queries across live chat, email, and phone promptly and professionally • Provide support to Chinese-speaking clients across UK and Canada coverage hours • Deliver high-quality support during evening shift operations, ensuring service-level agreements and response-time targets are met • Support clients through account opening, verification, funding, and withdrawal processes • Help clients navigate MT4, MT5, and the MultiBank-Plus platform • Escalate complex or sensitive cases to the relevant internal team and follow through to resolution • Keep accurate records of client interactions and contribute to knowledge-base improvements • Follow all compliance, KYC, and data-protection requirements

• Identify, approach and sign new Introducing Brokers, affiliates and partners across the assigned territory. • Onboard partners and equip them with the tools, materials and commercial terms to perform. • Manage and grow an existing portfolio of IB relationships, increasing the trading volume they generate. • Act as the main commercial contact for partners, resolving issues and identifying growth opportunities. • Track partner performance and report on pipeline, activations and volume. • Operate within the Group's regulatory and compliance framework for the relevant jurisdictions.

• Build end-to-end analytical models to evaluate customer lifecycle • Leverage outputs from ML models to drive predictive analytics and decision frameworks • Develop advanced segmentation models using clustering techniques and behavioral feature engineering • Perform deep funnel analysis using event-level data to identify inefficiencies and optimization opportunities • Design and evaluate experimentation frameworks with statistical rigor • Build data pipelines for analytics use cases using SQL and Python • Work with large datasets from multiple sources • Apply attribution modeling techniques to evaluate marketing performance • Translate complex datasets and model outputs into clear, commercially actionable insights • Automate recurring analyses and reporting using Python and workflow orchestration tools

• Design, train, and deploy machine learning models across use cases such as recommendation systems, churn prediction, fraud detection, and behavioral scoring • Build modular ML pipelines for feature engineering, training, validation, and inference • Implement deep learning and NLP models, including transformer-based architectures for text and sequence data • Develop and deploy LLM-based applications • Integrate models into production systems via REST/gRPC APIs and microservices • Implement MLOps pipelines using CI/CD, versioning, and monitoring tools • Monitor model performance, detect drift, and implement automated retraining strategies • Optimize models for latency, throughput, and cost in cloud environments • Work closely with Data Engineers to ensure scalable and efficient data access • Evaluate and integrate new AI frameworks and tools to continuously improve performance

• This role focuses on building the data foundations that enable advanced analytics and machine learning at scale. • You will design and develop data pipelines and architectures that support real-time insights and AI-driven applications across the business. • Working with large, complex datasets, you will ensure data is reliable, accessible, and optimized for both analytics and machine learning use cases. • Develop data models and warehouse schemas optimized for analytics and machine learning. • Build and maintain data ingestion frameworks using streaming systems (Kafka, Kinesis) and batch processing (Spark, Airflow). • Build and manage feature stores to support ML model training and inference. • Integrate data from multiple sources into a unified architecture. • Implement data quality validation frameworks and monitoring systems. • Optimize data pipelines for performance, scalability, and cost efficiency.

• Design and build scalable, low-latency dashboards that ingest data from data warehouses (e.g., Snowflake, Redshift, BigQuery) and real-time pipelines (e.g., Kafka, Kinesis). • Develop AI-integrated visualization layers that surface outputs from machine learning models such as churn prediction scores, LTV forecasts, behavioral clustering, and anomaly detection signals. • Implement semantic data layers and metric definitions using tools like dbt or LookML to ensure consistency across reporting. • Build natural language interfaces on top of dashboards using LLMs (e.g., OpenAI APIs, AWS Bedrock) to enable business users to query data conversationally. • Develop automated insight generation systems that summarize trends, highlight anomalies, and recommend actions using NLP/LLMs. • Optimize dashboard performance through efficient query design, caching strategies, and incremental data models. • Integrate visualization tools with backend APIs and ML services to enable dynamic, real-time updates. • Partner with ML Engineers to interpret model outputs and design visualization patterns that reflect uncertainty, confidence intervals, and predictions accurately. • Establish data governance practices including lineage tracking, metric validation, and monitoring.

• Architect, design, and develop advanced Android applications using Kotlin and modern Android frameworks. • Build highly performant, secure, and reliable features for global trading users. • Collaborate with product managers, designers, and backend engineers to define and deliver new capabilities. • Implement secure coding standards, encryption, and best practices for data protection. • Optimize application performance, memory usage, and responsiveness across a wide range of Android devices. • Integrate applications with backend APIs, WebSocket feeds, and third-party services. • Maintain a clean, scalable codebase following MVVM, Clean Architecture, and Jetpack best practices. • Write comprehensive unit tests, UI tests, and automation scripts to ensure application stability. • Participate in code reviews, mentor junior engineers, and enforce high engineering standards. • Stay up to date with the latest Android technologies, Google guidelines, and industry trends.

• Design and implement end-to-end test automation frameworks. • Build automated tests for web, mobile, and API layers. • Create and maintain CI/CD pipelines with automated test execution. • Perform load and performance testing on trading systems. • Work closely with developers to shift testing left in the development cycle. • Identify and track quality metrics and testing coverage. • Participate in release planning and go/no-go decisions.