BI Analyst – Credit Industry

SUMMARY:
Are you passionate about turning data into actionable insights that drive business decisions? Join a dynamic credit industry team where you will pitch, communicate, and deliver impactful solutions while working with cutting-edge data tools.

POSITION INFO:
Our client is a market leader in the credit industry, providing innovative solutions that empower businesses to make smarter lending and risk decisions. They are looking for a skilled BI Analyst who can own the full data lifecycle — from data cleaning and reworking, to visualizing and presenting actionable insights.

This is a full-time, office-based role where you will collaborate closely with business stakeholders, work with large and complex datasets, and deliver insights that directly impact business performance. If you enjoy solving problems, working with data, and influencing strategic decisions, then this opportunity is for you!

Key Responsibilities:

• Collect, clean, and rework data from multiple sources to ensure accuracy and completeness.
• Develop and maintain BI reports and dashboards to visualize key trends and metrics.
• Translate business needs into data-driven insights and communicate findings to stakeholders.
• Present and pitch insights in a clear, compelling way to influence decision-making.

• Bachelor’s Degree in Information Systems, Computer Science, Data Analytics, or a related field.
• 2–4 years’ experience as a BI Analyst or Data Analyst, preferably within the credit or financial services industry.
• Strong proficiency in SQL for data manipulation and querying.
• Experience with BI visualization tools (Power BI, Tableau, Qlik, or similar).
• Excellent communication skills – able to pitch and present data insights to both technical and non-technical audiences.
• Detail-oriented, analytical mindset with a passion for solving business problems using data.
• Full-time office-based role – must be comfortable working onsite daily.

• Actuarial roles (Life, Short-Term, Health, Pensions, and Quantitative)
• Data Scientists / Data Analysts (Python, R, SQL, and Machine Learning)
• Risk Analysts (Credit, Market, Model Risk, and Operational)
• Pricing Specialists (Insurance and Financial Products)
• Machine Learning & AI Data Scientists (ML Ops, NLP and Predictive Modelling)
• Quantitative Specialists across Banking, Insurance, and FinTech

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