Data Analyst and Banking Insights Specialist
Summary
Analyze banking datasets to uncover trends, risks, and growth opportunities, then translate findings into actionable insights for senior leadership using SQL, Python, and visualization tools.
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.