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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data analysis and solution development, particularly in credit, risk, and fraud applications. Proficient in translating complex data insights into actionable business strategies while effectively communicating with stakeholders at all levels.
Highest-signal resume keywords
Python ProficiencySQL ProficiencyData AnalysisA/B Testing ExperienceCommunication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
StatisticsEconometricsData ScienceAPIsSoftware Engineering ConceptsVersion ControlDeploymentTestingCausal InferenceReal-World Data Structures
Soft Skills
Strong Communication Skills
Industry Keywords
FintechHigh-Growth TechnologyCreditRiskFraudCustomer AcquisitionDecision WorkflowsData InfrastructureOperational TeamsC-Level Stakeholders
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Work embedded with clients to understand decision workflows, data infrastructure, and operations
- Identify pain points and shape them into actionable use cases for Avra's platform
- Build and deploy AI-powered solutions across credit and risk, customer acquisition, and fraud applications
- Assess customer data quality and accuracy
- Partner with the Data Platform team to ensure the right data is consumed correctly
- Work with a Deployment Strategist to turn technical insight into customer business solutions
- Translate business requirements into technical specifications and technical outputs into business narratives
- Participate in Avra's FDE cohort, benchmark use cases, and share learnings
- Bring field insights to product and engineering teams
- Drive rapid iteration based on real-world usage and feedback
- Communicate with data specialists, operational teams, and C-level stakeholders
- Build solutions that reach production quickly
Requirements
What you’ll need- Background in statistics, econometrics, or data science (degree or equivalent practical experience)
- 2+ years of hands-on experience solving real business problems with data in credit, risk, fraud, growth/acquisition, or an adjacent decision-heavy domain
- Proficiency in Python and SQL
- Comfort working with APIs and basic software engineering concepts, including version control, deployment, and testing
- Familiarity with real-world data structures and production data
- Experience with experimentation and causal inference, including A/B tests, incrementality, and quasi-experimental methods
- Strong communication skills and ability to present a model's business impact to senior executives
- Previous experience at a fintech or high-growth technology company is nice to have