The Role
Leads advanced data analysis across business areas, translating complex findings into actionable insights. Develops KPIs, dashboards, forecasts, predictive models, and statistical analyses; supports data modelling, data quality, and analytical controls. Partners with business and technical stakeholders, mentors analysts, improves analytical processes, and applies AI and GenAI tools. Banking or financial services knowledge is preferred, including risk analysis, financial products, regulations, and compliance.
Summary Generated by Built In
The Data Analyst role is
responsible for unlocking value from data by making complex information
accessible, meaningful and actionable for stakeholders across the organisation.
The role transforms data into insights that support strategic decision-making,
optimise operations and drive business performance.
The successful candidate will work across
multiple business areas, partnering with analysts, engineers, data scientists
and business stakeholders to understand business needs, translate these into
data requirements and deliver high-quality analysis, reporting and insights
Requirements
Key Responsibilities
- Conduct advanced data analysis across
multiple business areas to identify trends, patterns, opportunities and
potential data issues.
- Translate complex analytical findings into clear
business insights and recommendations for technical and non-technical
stakeholders.
- Lead data analysis projects, taking ownership of planning,
scoping, timelines, delivery and quality.
- Develop and maintain KPIs, reports, forecasting,
scenario analysis and dashboards to support informed decision-making.
- Apply advanced statistical techniques and develop simple
predictive models, following appropriate data science and analytical
lifecycles.
- Work closely with business and technical teams to
understand requirements, data flows, processes and downstream data needs.
- Act as a bridge between business stakeholders,
data analysts, engineers and data scientists.
- Challenge assumptions, vague requirements and
requests that may not address the underlying business need.
- Identify opportunities to improve processes, data
assets and analytical ways of working.
- Ensure data analysis is accurate, well documented,
repeatable and suitable for implementation with minimal rework.
- Support data modelling and data mart development,
ensuring data can be effectively used across multiple teams.
- Identify and address data quality gaps and
proactively challenge solution designs to ensure appropriate data
requirements are considered.
- Apply GenAI, AI and modern analytical tooling where appropriate to improve productivity and analytical outcomes.
- Mentor, guide and upskill less experienced analysts
in areas such as SQL, Python, data visualisation and analytical
standards.
- Participate in knowledge-sharing initiatives, code
reviews, interviews and subject matter guidance.
- Build strong relationships with stakeholders and
manage expectations, requirements and potential conflicts effectively.
Key Technical Requirements
- Significant experience in Data Analysis,
preferably within banking or financial services.
- Advanced proficiency in SQL, including
complex queries, query optimisation and working with large datasets.
- Strong Python or R skills, including data
manipulation and visualisation libraries such as pandas, NumPy, Matplotlib
or Seaborn.
- Advanced Excel, including macros and VBA.
- Strong Power BI, Tableau or similar data
visualisation and dashboarding experience.
- Advanced statistical analysis and modelling.
- Experience with predictive analytics and its
application to business/financial data.
- Knowledge of data modelling techniques and
data structures.
- Experience with data quality, validation and
analytical controls.
- Understanding of risk analysis and its
application within financial services.
- Knowledge of financial products, services, industry
trends, regulations and compliance considerations.
- Exposure to AI/GenAI and modern data/analytical
tools would be advantageous.
Experience &
Qualifications
- Proven experience delivering complex data
analysis projects and demonstrating business impact through
data-driven insights.
- Significant experience in data analysis, with
financial services/banking experience strongly preferred.
- Bachelor's or Honours Degree in Data,
Analytical, Technical or a related field.
Skills Required
- Significant experience in data analysis
- Advanced SQL proficiency, including complex queries, query optimization, and large datasets
- Strong Python or R skills, including data manipulation and visualization libraries
- Advanced Microsoft Excel, including macros and VBA
- Strong Power BI, Tableau, or similar data visualization and dashboarding experience
- Advanced statistical analysis and modeling experience
- Experience with predictive analytics applied to business or financial data
- Knowledge of data modeling techniques and data structures
- Experience with data quality, validation, and analytical controls
- Understanding of risk analysis in financial services
- Knowledge of financial products, services, industry trends, regulations, and compliance considerations
- Experience delivering complex data analysis projects and demonstrating business impact
- Bachelor's or Honours degree in Data, Analytical, Technical, or related field
- Banking or financial services experience
- Exposure to AI, GenAI, and modern data or analytical tools
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The Company
What We Do
Sabenza IT is a niche recruitment company specializing in Information Technology, SAP, Finance, and Engineering roles, with over 23 years of experience.
