Education & Experience Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related fieldMinimum of 5 years’ experience in data analysis or analytics rolesProven experience working with:Large and complex datasetsCross-functional teams (product, finance, operations, technology)Experience in financial services, fin tech, or lending environments is a strong advantage 2. Technical Skills (Non-Negotiable)Data Handling & Querying Advanced SQL,Experience with relational databases such as PostgreSQL or MySQLExperience with advanced excel Programming Strong proficiency in Python (preferred) Experience with data analysis libraries such as Pandas and NumPyFamiliarity with Scikit-learn or similar tools is an added advantage Data Visualization & BI Hands-on experience with Power BI or TableauAbility to:Build and maintain dashboardsDesign KPI tracking systemsPresent insights in a clear and compelling manner Data Modeling & Warehousing Strong understanding of data modeling concepts (e.g., star and snowflake schemas)Experience with ETL/ELT processesFamiliarity with tools such as dbt, Airflow, or equivalent 3. Analytical & Business Skills Ability to translate business problems into structured data analysesStrong experience defining, tracking, and interpreting KPIsProficiency in root cause analysis and problem diagnosisExperience with:Cohort analysisFunnel analysisForecasting and trend analysisUnderstanding of:A/B testing methodologiesStatistical significance and interpretation 4. Problem-Solving & Critical Thinking Ability to work with ambiguous or incomplete dataStrong capability in identifying and resolving data quality issuesStructured approach to solving complex and unstructured problemsHigh attention to detail, particularly in financial or operational contexts 5. Communication & Stakeholder Management Ability to present insights clearly to non-technical stakeholdersProven ability to influence decision-making using dataSkilled in simplifying complex analyses into actionable insightsExperience working with:Senior leadershipProduct and operations teams 6. Data Governance & Quality Experience with:Data validation and cleaning processesData integrity checksDocumentation of data definitions and standardsAbility to:Establish and maintain data quality frameworksEnsure consistency and reliability across multiple systems 7. Leadership & Ownership Ability to own analytics initiatives end-to-endExperience mentoring junior analystsDemonstrated ability to promote a data-driven cultureExperience leading:Reporting automation initiativesDashboard standardization efforts 8. Nice-to-Have Skills Exposure to machine learning concepts and techniquesExperience with APIs and data integrationsFamiliarity with cloud platforms such as AWS, GCP, or AzureAdditional exposure to:Real-time analytics systemsFraud detection or risk analytics environments

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Senior Data Analyst