MultiBank Group

• 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.

Role Description This role focuses on building the next generation of AI-powered insights, going far beyond traditional dashboards. Working with real-time data and machine learning outputs, you will create intuitive, high-impact visual products that enable faster, smarter decision-making across the business. The position is centered on turning complexity into clarity — surfacing trends, anomalies, and predictive signals in a way that drives action. With full ownership of the visualization layer, you will shape how data is consumed at scale, introducing new tools, ideas, and intelligent reporting approaches in a fast-paced, high-growth environment. Key Responsibilities - 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 - 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. Technical Requirements - Advanced proficiency in BI tools (Power BI, Tableau, Looker) with experience embedding dashboards and customizing via APIs. - Strong SQL with experience optimizing complex queries across large-scale datasets (billions of rows). - Experience working with modern data stacks: - Warehouses: Snowflake, Redshift, BigQuery - Transformation: dbt - Streaming: Kafka, Kinesis - Familiarity with Python for data manipulation (pandas, NumPy) and light backend integration. - Exposure to ML outputs and statistical concepts (classification, regression, clustering, anomaly detection). - Experience integrating LLMs / NLP pipelines into reporting workflows. - Understanding of data modeling (star/snowflake schemas) and performance tuning. - Experience with API integrations and embedding analytics into internal platforms. Benefits - Work with one of the world’s leading financial derivatives institutions. - Competitive salary plus performance-based incentives. - Access to a dynamic, international, and fast-growing environment. - Strong opportunities for career progression within a global financial group. - Be part of a business committed to innovation, excellence, and long-term growth. - Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.

• 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.

• Collaborate closely with cross-functional teams to design and develop user-friendly web interfaces for trading platforms. • Optimize web applications for maximum speed, security, and scalability in a real-time data environment. • Build and integrate REST APIs and WebSockets to facilitate seamless communication between front-end and back-end systems. • Utilize Tailwind CSS and other frameworks to create responsive, consistent designs that enhance user experience across devices. • Maintain brand consistency throughout the design process and ensure compliance with industry regulations. • Implement robust front-end security measures to protect against common vulnerabilities. • Stay updated with the latest industry trends and continuously improve the front-end architecture.

• Design and build advanced, secure, and responsive iOS applications for financial and trading platforms. • Collaborate with designers, backend developers, and product managers to define, develop, and ship new features. • Optimize app performance by implementing efficient algorithms and data structures. • Ensure the highest level of security and compliance by following secure coding and data protection best practices. • Integrate applications with backend APIs and third-party services to enhance functionality. • Maintain and improve the existing iOS codebase, ensuring scalability and maintainability. • Write and maintain unit tests, integration tests, and documentation to ensure reliability and stability. • Monitor application performance, identify bottlenecks, and implement optimization solutions. • Stay up-to-date with industry trends, frameworks, and development best practices. • Mentor junior developers, conducting code reviews and providing technical guidance.

• Design, develop, and maintain scalable backend solutions for CFD, FX, and crypto trading platforms • Collaborate with architects, product managers, and engineering teams to design robust, secure, and efficient systems • Implement server-side architectures that prioritize performance, security, and reliability • Develop high-throughput applications using concurrent and reactive programming methodologies • Focus on non-functional requirements such as performance optimization, scalability, and security • Estimate development efforts, define project scopes, and deliver within agreed timelines • Write and maintain technical documentation for backend systems and integrations • Test, debug, and optimize backend applications to ensure stability and responsiveness