Carefull - Data Scientist / AI Engineer

CAREFULL http://getcareful.com Carefull is an AI-powered financial safety platform that helps banks, credit unions, and wealth advisors protect older-adult customers from fraud and money mistakes. We help financial institutions maintain whole-family relationships while protecting their clients. Carefull’s technology addresses senior-specific financial safety challenges: our monitoring detects fraud patterns missed by industry-standard tools, and our features — identity-theft protection, password and document management, communication tools, and how-to content — help customers maintain financial independence while enabling loved ones to step in when needed. THE ROLE We are looking for a Data Scientist / AI Engineer to join our Data team to build, evaluate, and improve the AI-powered detection systems at the core of our product. You will work on systems that analyze financial transactions and decide whether to alert a family about potential concerns. This is a hands-on role: you’ll research fraud patterns, design detection logic, write production code, and rigorously evaluate system performance. You will own features end-to-end: from problem understanding to implementation, deployment, and measurement. WHAT YOU’LL DO - Own end-to-end implementation of AI-driven detection features, from discovery to production deployment and iteration. - Design and build data enrichment pipelines to extract structured information from messy, real-world financial transaction data. - Research fraud and scam typologies relevant to older adults and translate findings into scalable detection logic. - Build evaluation frameworks (metrics, error analysis, model comparisons) to measure system performance and drive improvement. - Optimize AI pipelines for accuracy, latency, and cost, making informed tradeoffs on model selection and architecture. - Collaborate with Customer Service, Go-to-Market, and partner-facing teams to ensure solutions meet real-world needs and deliver measurable impact. - Stay current with developments in LLMs, agent architectures, and applied AI, and identify practical applications for our domain. WHO YOU ARE Required - Strong Python skills with experience building data pipelines and production systems. - Hands-on experience with LLMs in production: designing workflows, handling structured outputs, managing context, and evaluating performance. - Experience with evaluation methodology: precision/recall tradeoffs, confusion matrices, error analysis, statistical significance. - Ability to work with messy tabular data (time series, inconsistent categorical labeling, incomplete records). - Comfortable reasoning about ambiguity and building systems that handle context-dependent answers. - Clear written and verbal communication in English; able to document reasoning and explain technical decisions to non-technical stakeholders. Strong Plus - Experience with LangChain, LangGraph, or similar agent orchestration frameworks. - AWS experience (Lambda, CDK, Bedrock, Redshift, DynamoDB). - Background in fraud detection, financial services, or risk/compliance. - Experience with financial transaction data (ACH, Zelle, wire transfers, POS data, merchant categorization). - Familiarity with cost optimization for LLM-based systems at scale. Nice to Have - Experience working with regulated industries or bank partners. - Exposure to elder care, aging-in-place, or financial vulnerability research. - Background in data science or ML beyond LLMs (statistical modeling, anomaly detection). INTERVIEW PROCESS - Silver Screening interview - Take-home challenge - Client technical interview - CTO interview - Final interview Hiring Manager