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Actuarial Interns support insurance and financial-services teams through quantitative analysis, data transformation, modeling, tool and process development, pricing, risk and performance analysis, financial reporting, and automation. They collaborate with actuarial, finance, technology, and analytics professionals while developing practical expertise under mentorship. Assignments may span life, group, pension, investment, auto, home, data science, analytics, and artificial intelligence functions.

Design and develop intelligent agents, copilots, conversational experiences, generative AI solutions, RAG architectures, and automations. Integrate AI solutions with business systems, develop prototypes, support production deployment, and implement governance, security, CI/CD, testing, monitoring, and continuous improvement. Collaborate with analysts, architects, security teams, and business partners to deliver measurable business value. Advanced French and intermediate English proficiency are required.

Designs, develops, integrates, and evolves generative AI solutions including conversational assistants, intelligent agents, and automation products. Builds interfaces, APIs, services, and enterprise integrations; contributes to RAG, semantic search, prompting, context management, and agent orchestration architectures. Ensures security, compliance, privacy, reliability, observability, testing, and production readiness. Provides technical leadership to delivery teams and collaborates with stakeholders to integrate AI into business processes and technology standards.

Processes life insurance applications from submission through policy issuance and commission settlement. Responsibilities include ordering and tracking underwriting requirements, reviewing documentation and mail, entering data in WealthServ, preparing submissions, coordinating between advisors and insurance carriers, following up on outstanding requirements, resolving underwriting issues, verifying policy accuracy, and maintaining timely status updates while meeting service standards.

Conduct actuarial analyses for personal auto and home insurance pricing, including rate indications, segmentation, algorithm adjustments, KPI monitoring, and market-driven recommendations. The role transforms large datasets into actionable insights, communicates findings to stakeholders, supports pricing and process-improvement initiatives, mentors analysts, and represents actuarial in cross-functional groups.

Process life insurance applications end-to-end, ensuring timely, accurate issuance and settlement of policies. Liaise with advisors and carriers, order underwriting requirements, update WealthServ, resolve underwriting issues, and maintain data accuracy and advisor communication.

Provide personalized wealth planning, investment advice, and insurance recommendations to clients nationwide via virtual channels. Build and grow client relationships, execute trades, ensure compliance, maintain accurate client records, and collaborate with partners to drive business growth.

Designs functional and technical IT solutions, including workflows, business rules, integrations, and AI-enabled products. Collaborates with architects, developers, business analysts, QA teams, and business partners to align solutions with architecture and standards. Supports estimation, planning, testing, defect analysis, deployments, and production activities while maintaining documentation. Mentors colleagues and promotes knowledge sharing. The role requires experience with complex application environments, Agile/Scrum, Azure-based development, and technologies including .NET, databases, messaging platforms, containers, and mainframes.

Develop and scale investment-focused analytical data products, including financial datasets, ETL/ELT pipelines, dbt models, semantic layers, Power BI reports, and Streamlit applications. Partner with investment teams to translate quantitative requirements into reliable, governed, cloud-native solutions. Own products throughout their lifecycle, implementing data quality controls, orchestration, monitoring, documentation, and operational support. Contribute to AI-ready datasets and analytics modernization across portfolio management, performance, risk, trading, and research workflows.

Build and support production-grade quantitative technology solutions for investment teams. Partner with quants, researchers, traders, and portfolio managers to translate analytical workflows into reusable Python software, data pipelines, libraries, and platform capabilities. Contribute to cloud-native development, AI-enabled workflows, orchestration, monitoring, data quality, deployment, incident resolution, and platform standardization. The role requires quantitative literacy, strong software engineering, collaboration, ownership, and experience supporting analytics or investment technology environments.