Data Analyst Executive

About Us:

We are a dynamic and fast-growing financial technology group headquartered in Manchester, United Kingdom, with an established presence across the UK, Europe, Canada, Australia, Pakistan, and Bangladesh. Our group, encompassing ACE Money Transfer and ACE Union, operates across two regulated verticals: Electronic Money Services (EMI) and Cross-Border Remittances.

Through our digital platforms, including mobile apps, web portals, and APIs, we deliver a comprehensive range of regulated financial services. These include digital payments, e-wallets, electronic money issuance, prepaid cards, mobile top-ups, bill payments, and international money transfers, designed to serve both individual and business customers in over 100 countries. By leveraging cutting-edge technologies such as AI for fraud detection, automation for seamless transactions, and partnerships with global leaders like Mastercard, we provide secure, user-friendly, and accessible financial solutions that adapt to the evolving needs of a global customer base.

As we scale our EMI and remittance operations amid 2025's fintech landscape—marked by real-time payments, embedded finance, blockchain integration, and sustainability initiatives—we are building a leadership team to drive innovation, regulatory compliance, and excellence across our dual-regulated ecosystem.

Position Summary:

We are seeking a highly analytical and business-oriented Data Analyst to join our analytics division. This role is focused on transforming raw data into actionable insights that drive strategic decisions across the organization. The ideal candidate will have strong expertise in Power BI, data modeling, and translating complex datasets into intuitive dashboards and reports . A deep understanding of data relationships, visual storytelling, and a passion for enabling decision-making through data is essential.

Duties & Job Responsibilities:

• Design and develop interactive dashboards and reports using Power BI to deliver actionable insights aligned with business objectives
• Build robust data models in Power BI using DAX and industry best practices to enable scalable and efficient reporting
• Analyze large and complex datasets to uncover trends, patterns, and performance indicators that inform strategic and operational decisions
• Work closely with cross-functional stakeholders to understand requirements and translate them into effective data solutions
• Maintain high standards of data quality and integrity by validating sources, ensuring accurate transformations, and monitoring refresh pipelines
• Support the development of analytics by creating reusable datasets, promoting data literacy, and enabling business users
• Leverage SQL and Python for data manipulation, transformation, and automation of recurring analytics tasks
• Experience with data science techniques such as regression, classification, clustering, or forecasting is a strong plus and can support advanced analytical use cases
  
  

Education:

Bachelor’s degree in computer science, Finance or any related field

Experience:

2-3 Years of working experience in the relevant field.

Behavioral Skills:

• Problem-Solving Skills: Ability to approach challenges logically and find effective solutions
• Adaptability: Willingness to embrace change and learn new tools or methods
• Collaboration: Strong team player with a focus on building positive working relationships
• Communication: Clear and concise communication, both written and verbal, to convey complex ideas effectively
  
  

Competencies:

• Power BI Expertise: Proficiency in building impactful dashboards, data models, and visualizations using DAX and Power BI best practices to drive business insights
• Data Analysis & Insight Generation: Strong analytical skills to interpret large, complex datasets and transform them into actionable insights that support strategic decisions
• Data Modeling: Experience in designing efficient, scalable data models tailored for performance and usability in BI environments
• Programming Skills: Experience in Python, SQL, and scripting for data manipulation and analysis
• Cloud Computing: Knowledge of cloud platforms, particularly AWS, for data storage and processing
• Automation: Hands on experience with Power Automate to optimize workflows and automate tasks
• Data Science Foundations (Plus): Exposure to data science techniques such as regression, clustering, or forecasting is a valuable plus for enabling predictive insights
  
  

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