Customer Success Analyst

Requirements: Experience in data analytics, analytics engineering, or a related fieldExperience in a customer-facing roleEveryday fluency with AI tools, including using LLMs to accelerate analysis, create monitoring agents, and automate manual workStrong SQL skillsProficiency in Python for data pipelines, automation, and reportingExperience with business intelligence tools such as Sigma, Tableau, or Power BIStrong attention to detail and ability to identify anomaliesAbility to present complex findings to technical and non-technical audiencesAbility to work independently, take ownership of outcomes, and solve problems persistently A customer-first approach, with confidence speaking with customers, leading meetings, and building trust around their dataAlignment with our core values: be the expert, pitch in, and get it donePreferred: BA or BS in Computer Science, Data Science, or a related fieldPreferred: Familiarity with machine learning concepts and measuring model performance in productionPreferred: Experience with dbt or similar data transformation frameworks; dbt Fundamentals course completion is a plusPreferred: Experience in lending, fraud detection, or financial services dataPreferred: Experience resolving data issues directly with customers or external stakeholdersPreferred: Familiarity with AWS services, particularly CloudWatch and log analysis

Responsibilities: Proactively monitor customer data health and identify which accounts have healthy or deteriorating data, and whyWork with customers to resolve missing, incomplete, or inaccurate input data, owning each issue from detection through resolutionPrepare and present analysis for quarterly and monthly business reviews and executive or board reportingExplain complex data findings clearly to customers, executives, and engineersCoordinate with Customer Success Managers, fraud strategists, data science, and engineering to resolve customer issues and keep teams alignedBuild and monitor measures of customer data quality, score distributions, fill rates, alert firing rates, and model performance, including PSI, AUC, and score drift, using Sigma, Validio, and other AI toolsReplace manual reporting and monitoring with scheduled pipelines and AI-assisted workflows to scale coverageDesign, build, automate, and maintain internal and customer-facing reports and dashboardsAnalyze fraud and default data to help develop loan automation and fraud prevention strategies for customersOwn company reporting, including board-level internal reporting, fraud strategy analysis, and monthly reports for customers

Technologies: AIAWSBusiness IntelligenceCloudWatchMachine LearningPower BIPythonSQLTableaudbtCloud More: We are Point Predictive, based in San Diego, California, and are hiring a Customer Success Analyst for our in-person team at our San Diego headquarters. This customer-facing role combines technical analysis, AI and automation, and customer communication to help ensure our fraud detection models work effectively for each customer. We offer a salary starting at $100,000 per year, along with 401(k), dental, health, vision, life insurance, flexible spending and health savings accounts, paid time off, and stock options. last updated 44 week of 2026