Role Description We’re seeking a Senior Actuarial Analyst to support the Medical Economics Enablement team by turning complex healthcare data into actionable insights that improve affordability and inform strategic decision-making. This role partners closely with business, actuarial, and technical teams to design and deliver reports, dashboards, scorecards, and other analytic solutions that help identify cost drivers, evaluate performance, and support enterprise priorities. Using strong actuarial knowledge and sound judgment, the analyst gathers requirements, defines business rules, and develops Business Intelligence solutions that align with operational needs and actuarial standards of practice. - Develops reporting structure, toolset and analytic strategy to support market and domain teams as well as pricing for programs and products. - Supports the rating process by determining the need for and building actuarial model enhancements. - Distributes established reports and responds to inquiries. Supports the investigation of trends and anomalies. - Coordinate and independently develop BI content (reports, dashboards, scorecards, more complex analytic solutions) through the entire development life-cycle to provide data necessary to effectively make business decisions and measure goal attainment and overall performance. - Share expertise with business areas to assist in understanding enterprise data content, definitions and usage and the available BI tools. Maintains robust knowledge of data assets and tools and supports development/maintenance of a formal Knowledge Base. - Plans, implements, manages and/or contributes to projects that are moderate/high complexity. - Is a participant in good standing in the Actuarial Development Program. Qualifications - Bachelor's degree or advanced degree (where required). - 4+ years of experience in relevant actuarial experience. Related experience may be considered. - Must have completed 5 or more exams towards the eventual attainment of the ASA designation. - In lieu of meeting minimum exam requirements, may consider additional relevant experience. - In lieu of meeting minimum experience requirement, may consider ASA or more exams towards the eventual attainment of ASA. Requirements - Commercial and Medicare Healthcare knowledge – Highly Preferred. - Experience with risk modeling/normalization, outlier analysis and benchmarking. - Experience with Business Intelligence (BI) software – preferably Power BI. - Experience with MS suite and Power tools (Power Automate, etc.) – nice to have. - SQL (required), Python/R, automation/workflow software like Alteryx (nice to have). - Strong communication/storytelling abilities. Benefits - The opportunity to work at the cutting edge of health care delivery with a team that’s deeply invested in the community. - Work-life balance, flexibility, and the autonomy to do great work. - Medical, dental, and vision coverage along with numerous health and wellness programs. - Parental leave and support plus adoption and surrogacy assistance. - Career development programs and tuition reimbursement for continued education. - 401k match including an annual company contribution. Salary Range At Blue Cross NC, we take great pride in a fair and equitable compensation package that reflects market-price and our starting salaries are typically planned near the middle of the range listed. Compensation decisions are driven by factors including experience and training, specialized skill sets, licensure and certifications and other business and organizational needs. Our base salary is part of a robust Total Rewards package that includes an Annual Incentive Bonus*, 401(k) with employer match, Paid Time Off (PTO), and competitive health benefits and wellness programs. *Based on annual corporate goal achievement and individual performance. $98,092.00 - $156,947.00 Skills - Actuarial Analysis - Actuarial Consulting - Actuarial Science - Business Analysis - Complex Project Management - Financial Modeling - Hiring Management - People Management - Risk Assessments - Valuation Analysis

Role Description The Staff AI Product Analyst will define AI-native product analytics for Angi, turning visionary technology into prioritized use cases, robust evaluation disciplines, and a trusted data ecosystem. This role is central to building Angi’s agentic product analytics capability—defining where AI-native analytics creates real leverage, designing the evaluation frameworks that earn organizational trust, and establishing repeatable system standards. As a senior individual contributor, you will have broad influence across the product analytics function and beyond, ensuring that both human teams and AI agents remain aligned on truth, quality, and usefulness. The ideal candidate is a systems-thinking data expert who bridges the gap between deep AI capabilities and practical business outcomes. What you’ll do - AI Product Strategy & Metrics Design - Flagship Journey Measurement: Partner with AI product, engineering, and domain experts to define north-star and guardrail metrics for flagship AI journeys, focusing on adoption, task completion, quality, and downstream business outcomes. - Causal Framing & Experimentation: Align closely with data science partners on test design, interpretation, and causal framing when new AI products ship. - Data Layer Systems Thinking: Map how agents interact with metrics, raw tables, documentation, and APIs to ensure requirements for data and analytics engineering are explicit, structured, and testable. - Evaluation, Governance & Backlog Management - Eval Framework Architecture: Design and maintain formal evaluation sets, "golden datasets," rubrics, and regression checks for agent outputs to guarantee accuracy, completeness, policy safety, and usefulness. - Taxonomy & Failure Mode Analysis: Systematically categorize wrong answers, tool misuse, context gaps, and data edge cases, feeding those insights back into prompts, retrieval (RAG), tools, and data modeling pipelines. - Performance Monitoring: Monitor live usage of Agentic AI analytics workflows—tracking success, abandonment, fallback patterns, and human override rates to maintain a prioritized engineering improvement backlog. - Cross-Functional Leadership & Enablement - Playbooks & Narrative: Own internal documentation defining when to use agents, required human checkpoints, and how to communicate uncertainty. Support enablement and leadership storytelling around agentic AI analytics. - Strategic Collaboration: Partner with business leaders, the Principal Analytics Engineer, and data engineering teams to translate complex AI capabilities into measurable business outcomes. - Defining Success: Deliver recurring measurement artifacts (dashboards, reviews, or written readouts) that leadership uses to prioritize roadmaps, while continuously reducing high-severity incidents where agents produce incorrect metrics. Qualifications - 10+ years of experience across product analytics, data science, or technical product management within a complex, high-scale operating environment. - 1+ years of direct, hands-on experience working with AI/LLM systems in an applied context, with a specific focus on evaluating, trusting, and deploying them responsibly. - Deep technical proficiency with Python, ML frameworks, data visualization/analytics platforms, and standard data management/governance practices. - Proven track record designing AI evaluation frameworks, including formal evals, golden datasets, production monitoring, or equivalent rigor in a related data discipline. - Exceptional communication skills with a demonstrated ability to translate highly technical AI insights and tradeoffs into clear narratives for non-technical business stakeholders. Preferred Qualifications - Experience building or evaluating agentic analytics workflows, orchestration frameworks, and familiarity with multi-agent systems. - Demonstrated ability to operate fluidly in ambiguity, run structured experiments or pilots, and default to fast action and iteration. - A systems-oriented mindset with a healthy skepticism of AI hype, focusing strictly on organizational outcomes and driving technical investments that yield true business value. Compensation & Benefits - The salary band for this position ranges from $165,000 - $225,000 commensurate with experience and performance. Compensation may vary based on factors such as cost of living. - This position will be eligible for a competitive year-end performance bonus & equity package. - Full medical, dental, vision package to fit your needs. - Flexible vacation policy; work hard and take time when you need it. - Pet discount plans & retirement plan with company match (401K). - The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world.

Role Description Atuar de forma estratégica na evolução de produtos de Scores de Fraude, KYC, contribuindo com decisões orientadas por dados, excelência na execução e impacto nos resultados de clientes globais e locais, ao mesmo tempo desenvolvendo-se como futura referência no tema. Responsibilities - Atuar na gestão de produtos de Fraud Scores, KYC e soluções relacionadas, participando de todo o ciclo de vida — da descoberta à entrega e mensuração de resultados. - Contribuir na definição e evolução da visão e estratégia do produto. - Construir e priorizar backlog e roadmap utilizando análises de dados e feedbacks. - Conduzir iniciativas de discovery técnico e funcional em parceria com Engenharia, Dados e áreas de risco. - Apoiar decisões considerando risco, conversão, experiência do usuário e eficiência operacional. - Entender, propor e acompanhar performance dos produtos. - Acompanhar tendências de fraude, regulação e mercado. - Atuar com stakeholders comunicando resultados, hipóteses e aprendizados. - Elaborar reports executivos, ser owner de fóruns para dar visibilidade das evoluções, entregas e valores agregados gerados ao mercado. Qualifications - Experiência de 3–5 anos em Gestão de Produtos. - Conhecimento em SQL e Excel; Python desejável. - Vivência com produtos data-driven e experimentação. - Capacidade de compreender APIs e integrações técnicas. - Habilidade analítica e de tomada de decisão. - Boa comunicação e storytelling com dados. - Conhecimento de metodologias ágeis. - Inglês intermediário. - Formação Superior em Administração, Economia, Engenharia de dados, Ciência da Computação ou áreas correlatas. - Habilidades de comunicação, negociação e liderança colaborativa. - Conhecimento de metodologias ágeis na gestão de produtos. - Experiência em gestão de produtos com tomadas de decisões baseadas em dados. Benefits - Compromisso em construir uma cultura inclusiva e um ambiente equilibrado entre carreira e interesses pessoais. - Reconhecimento como uma das melhores e mais inovadoras empresas para se trabalhar no país. - Premiações pelo Great Place To Work™ em 24 países e pela certificação internacional Top Employers. - Reconhecimento como uma das melhores empresas para jovens profissionais. - Avaliação de 4,6 no Glassdoor.

• Own and analyze the end-to-end user funnel — from discovery through to checkout — identifying opportunities to improve conversion, user experience, and revenue performance • Define KPIs and measurement frameworks for product initiatives and business performance, ensuring the right metrics are in place to drive meaningful decisions • Lead the design and analysis of A/B tests, including hypothesis definition, metric selection, and impact evaluation • Build and evolve the data foundations — event tracking, core metrics, and data definitions — in partnership with Data Engineering • Develop dashboards and monitoring tools that provide ongoing visibility into product and business performance • Conduct deep-dive analyses to identify trends, anomalies, and performance gaps, translating findings into clear, actionable recommendations • Serve as a trusted analytical voice within the business — actively shaping strategy, challenging assumptions where the data demands it, and influencing key decisions with well-reasoned, evidence-based narratives • Establish scalable methodologies for measuring product and business performance across online and offline channels • Partner closely with Product Managers and global stakeholders to prioritize opportunities and influence roadmap decisions • Apply statistical rigor to experimentation, including power analysis, sample size estimation, and result interpretation