Data Intelligence Consultant
Listed on Experian’s official careers site. Posted October 6, 2026. Check that it is still open and apply there.
Apply on Experian’s careers site →Job description
We are looking for a Data Management Analyst who will be responsible for transforming data into actionable insights to support business decision-making. The ideal candidate will have hands-on experience with data tools, and the ability to manage stakeholders while driving data-driven strategies.
Key Responsibilities
Analyze large datasets to identify trends, patterns, and actionable insights Design, develop, and maintain dashboards and reports for business stakeholders Work with cross-functional teams to understand business requirements and translate them into analytics solutions Develop and optimize data models, KPIs, and performance metrics Support business planning through forecasting, trend analysis, and performance tracking Ensure data accuracy, integrity, and consistency across reports Automate repetitive reporting processes using tools and scripts Present insights and recommendations to management in a clear and actionable manner Mentor junior analysts (if applicable) and ensure best practices in analytics Growth Opportunities Opportunity to lead larger analytics projects and teams Exposure to advanced analytics and data science initiatives Career progression into Senior Analytics Manager / Data Lead roles
Qualifications
- Bachelor's degree in Engineering, Statistics, Mathematics, Economics, or related field 4–7 years of experience in analytics, business intelligence, or data roles
- Strong proficiency in: SQL, Python, Pyspark Excel (advanced functions, pivot tables, etc.) Data visualization tools (Power BI, Tableau, or similar) Good understanding of data modeling and ETL processes Working knowledge of Python or R for data analysis
- Ability to interpret data and provide business insights Experience in Data Intelligence / Business Intelligence environments Exposure to cloud platforms (Azure, AWS, or GCP) Experience working with large datasets and data warehousing concepts Basic understanding of machine learning concepts (optional but desirable)
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