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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates strong analytical capabilities with expertise in SQL, Python, and statistical analysis to drive data-driven decision-making. Proficient in building dashboards and conducting experiments to provide actionable insights across various business functions.
Highest-signal resume keywords
Strong SQL ExpertiseProficiency In PythonStatistical AnalysisExperience With BI ToolsUnderstanding Of Credit Risk
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonStatistical AnalysisHypothesis TestingExperimental DesignData ManipulationCustomer Lifecycle AnalyticsAutomated TestingData ModelingMachine Learning
Soft Skills
Influencing StakeholdersCross-Functional CollaborationClear Communication
Tools & Technologies
LookerTableauDatabricksBig Data TechnologiesCloud Platforms
Industry Keywords
Financial ServicesFintechBankingCredit RiskGDPRData Governance
Tech Stack
Tools & technologiesCloudPySparkPythonSQLTableau
About the role
Key responsibilities & impact- Collect, clean, and analyze data from multiple sources to support business needs
- Build and maintain core analytical datasets and reports for cross-functional teams
- Ensure data accuracy, consistency, and reliability through validation and quality checks
- Apply statistical and analytical techniques to uncover trends and opportunities
- Collaborate with business stakeholders to understand requirements and deliver actionable insights
- Conduct in-depth analyses on customer behavior, product usage, and market trends
- Translate complex data findings into clear recommendations for business strategy
- Support data-driven decision-making across marketing, operations, finance, and product teams
- Develop dashboards and KPI tracking tools to monitor business performance
- Design and execute experiments, including A/B tests, to evaluate initiatives
- Present insights to technical and non-technical audiences
- Promote data literacy and help colleagues use analytical tools
- Share best practices in data analysis, visualization, and reporting
- Contribute to documentation and training
- Dedicate time to cross-team projects that enhance company-wide data capabilities
Requirements
What you’ll need- Strong SQL expertise including complex queries, CTEs, window functions, and optimization
- Proficiency in Python or PySpark for data manipulation and analysis
- Solid foundation in statistical analysis, hypothesis testing, and experimental design
- Experience with BI tools (Looker preferred, Tableau, or similar)
- Experience with Databricks
- 2+ years experience in financial services, fintech, or banking environment
- Understanding of credit risk, lending products, and regulatory requirements
- Knowledge of GDPR and data governance
- Experience with customer lifecycle analytics and retention strategies
- Ability to make strategic and operational decisions using data
- Ability to tackle complex problems involving business, regulatory, and operational variables
- Exceptional ability to influence stakeholders and present data convincingly
- Experience working cross-functionally with non-technical teams
- Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, or related quantitative field is preferred
- Experience with big data technologies and cloud platforms
- Machine learning and AI knowledge
- Previous experience in high-growth startup environments
- Familiarity with data modeling using statistical algorithms
- Experience building automated testing and monitoring systems