As the Risk and Finance Data Analyst, you'll be the dedicated intelligence function to Risk. You’ll work closely with department leads, heads and managers, developing tools and insights that drive strategic initiatives. With a hands-on approach, you’ll explore complex datasets, derive actionable insights, and drive impactful projects.
Your role will require a blend of technical expertise, business acumen, and leadership to ensure the effective use of data science methodologies and the successful execution of key strategies.
Key Responsibilities:
- Strategic Insights: Partner with Risk and Finance leaders to develop the intelligence roadmap that aligns with organizational goals, prioritizing high-impact projects
- Build compelling and action-driving intelligence: Work with the team to deliver meaningful insight that drives measurable outcomes and can be used to inform decision-making and drive business growth.
- Risk Assessment and Quantification: Support the risk management team in assessing and quantifying potential risks across various business units.
- Data Analysis: Perform exploratory data analysis (EDA), feature engineering, and model development to tackle challenges such as fraud detection
- Financial Analysis: Analyse financial data, including revenue, costs, and profitability. Perform financial modelling and forecasting to support commercial decision-making.
- Data Visualisation: Own and maintain risk dashboards and reports to communicate key risk metrics and trends to stakeholders.
- Regulatory Compliance: Monitor and ensure compliance with relevant risk and financial regulations and industry standards.
- Risk Reporting: Prepare and present risk reports to senior management and regulatory bodies.
- Cross-functional Collaboration: Work closely with product, operations, risk, and revenue teams to translate data insights into actionable strategies that drive business performance.
What you’ll need:
- 4+ years of data analytics experience, preferably covering risk and/or finance
- Proficiency in analysing complex datasets, extracting meaningful insights, and identifying patterns, trends and anomalies using statistical techniques and tools such as Excel, SQL, Python, or R, and advanced data visualisation tools (e.g. Power BI, Tableau)
- Experience with cloud data platforms like Snowflake, Redshift, or Big Query
- Ability to develop and validate risk models using statistical and econometric methods.
- Ability to communicate complex risk and financial concepts and findings to both technical and non-technical audiences.
What they offer:
- Dynamic working environment in a extremely fast growing company
- Ample opportunity to grow and learn
- Hybrid working environment
- Flexible working
- Unlimited holiday