Data Analyst and Banking Insights Specialist

Location: UAE – AbuDhabi Full Time / On-site Experience: 4–7+ years Industry: Banking / Financial Services Who are we? Crayon Data is a leading provider of AI-led revenue acceleration solutions, headquartered in Singapore with a presence in India and the UAE. Founded in 2012, our mission has always been to simplify the world’s choices. Today, we’ve evolved into Tangram.ai — a modular, GenAI-powered platform built for the enterprise. Tangram lets organizations assemble intelligent agents, solutions, and models like building blocks to create, scale, and adapt AI-powered capabilities with speed, security, and precision. It’s not just a platform,it’s the operating layer for GenAI in the enterprise. Role Overview We are looking for a strong Data Analyst and Banking Insights Specialist to support a bank’s Command Unit, working closely with senior leadership to identify, develop and communicate high-impact business insights. The role will involve working with large and complex banking datasets across customers, products, transactions, channels and operations to identify trends, emerging issues, growth opportunities and areas requiring management attention. This is not a traditional reporting role. The individual is expected to go beyond dashboards and numbers to answer questions such as “What is happening?”, “Why is it happening?”, “What should management pay attention to?” and “What action should be taken?” Key Responsibilities · Analyse large-scale banking datasets across areas such as customer behaviour, deposits/liabilities, cards, lending, transactions, channels, revenue and operations. · Proactively identify business trends, anomalies, risks, growth opportunities and emerging patterns relevant to senior management. · Develop insightful analysis on topics such as customer acquisition, engagement and attrition; balance and revenue movements; customer and portfolio quality; product penetration; transaction and channel behaviour; and operational performance. · Convert complex data analysis into clear management insights and actionable recommendations. · Perform drill-down and root-cause analysis to explain the drivers behind movements in key business metrics. · Build compelling CXO-level insight packs, presentations and visualisations that communicate the business story clearly and concisely. · Respond to ad-hoc questions from leadership by rapidly analysing data and developing fact-based answers. · Work closely with business, analytics, data engineering and technology teams to identify the right data sources and validate findings. · Develop reusable analytical frameworks, datasets and dashboards to enable continuous monitoring of important business indicators. · Where relevant, use statistical analysis, segmentation, pattern recognition and predictive techniques to generate forward-looking insights. Required Skills & Experience · 4–7+ years of experience in data analytics, business analytics or insights roles. · Strong hands-on analytical capability with SQL and Python, including working with large and complex datasets. · Experience analysing banking or financial-services data, preferably covering customer, transaction, product, deposits, lending, cards, risk or operational datasets. · Strong ability to identify patterns and translate data into a business narrative, rather than simply reporting metrics. · Good understanding of statistical analysis, segmentation, trend analysis and root-cause analysis. · Ability to independently structure ambiguous business questions and determine the analysis required to answer them. · Strong communication and presentation skills, with the ability to explain complex findings to senior, non-technical stakeholders. · Strong PowerPoint/storytelling capability and experience creating management-level presentations. · Ability to work in a fast-paced environment where analysis may need to be turned around quickly for leadership discussions. Preferred / Nice to Have · Previous experience in a bank strategy, CEO office, command centre, management information, business intelligence or advanced analytics team. · Experience working directly with senior management / CXO stakeholders. · Knowledge of Power BI, Tableau or similar visualisation tools. · Exposure to predictive modelling / machine learning within banking. · Familiarity with modern data platforms such as Azure, AWS, Databricks, Cloudera or Spark. What We Are Looking For The ideal candidate combines three capabilities: Strong Data Analyst – Can independently work with complex datasets using SQL/Python and uncover patterns. Strong Banking Thinker – Understands what the numbers mean for the bank and can identify the questions leadership should be asking. Strong Storyteller – Can turn detailed analysis into a simple, compelling management narrative with clear implications and recommended actions. This role is best suited for someone who enjoys discovering the story behind banking data and using it to influence business decisions, rather than focusing primarily on recurring reporting and dashboard development. Pls note,looking for candidates who are based out in UAE Show more Show less

4–7+ years of experience in data analytics, business analytics or insights roles; strong hands-on analytical capability with SQL and Python; experience analysing banking or financial-services data; ability to translate data into a business narrative; good understanding of statistical analysis, segmentation, trend analysis and root-cause analysis; ability to independently structure ambiguous business questions and determine the analysis required; strong communication and presentation skills including PowerPoint/storytelling.

Analyze large-scale banking datasets across areas such as customer behaviour, deposits/liabilities, cards, lending, transactions, channels, revenue and operations. Proactively identify business trends, anomalies, risks, growth opportunities and emerging patterns relevant to senior management. Develop insightful analysis on topics such as customer acquisition, engagement and attrition; balance and revenue movements; customer and portfolio quality; product penetration; transaction and channel behaviour; and operational performance. Convert complex data analysis into clear management insights and actionable recommendations. Perform drill-down and root-cause analysis to explain the drivers behind movements in key business metrics. Build CXO-level insight packs, presentations and visualisations that communicate the business story clearly and concisely. Respond to ad-hoc questions from leadership by rapidly analysing data and developing fact-based answers. Work closely with business, analytics, data engineering and technology teams to identify the right data sources and validate findings. Develop reusable analytical frameworks, datasets and dashboards to enable continuous monitoring of important business indicators. Where relevant, use statistical analysis, segmentation, pattern recognition and predictive techniques to generate forward-looking insights.