• AI-alapú megoldások fejlesztése, tesztelése és bevezetése • ESG riportálási folyamatok automatizálása (CSRD, EU Taxonomy környezetben) • Adatfolyamok kialakítása és optimalizálása • ESG adatforrások azonosítása és integrálása • Dashboardok és vizualizációk készítése (pl. Power BI) • ESG teljesítmény monitorozása és elemzése • Szoros együttműködés IT, sustainability és nemzetközi stakeholder csapatokkal

• Take the product vision provided by leadership and write detailed, technical Product Requirement Documents (PRDs) • Use LLMs, Python, or low-code tools to build "Proof of Concept" features • Directly implement AI agents or automations that solve specific business problems • Dive into our Billing, CRM, Onboarding, lead gen, and Marketing stacks to find bottlenecks • Ensure our internal systems talk to each other • Relentlessly look for ways to use AI to reduce operating costs and increase speed of delivery across all departments • Handle a high volume of varying tasks daily

• Lead the transformation of the Claims operational model into an AI-native ecosystem. • Design, implement, and continuously optimize a hybrid operating model that blends AI agents and human operators. • Partner with operational leaders to reimagine service delivery through AI-native design principles. • Define orchestration models and accountability frameworks for hybrid human–AI work. • Implement monitoring frameworks to track AI agent performance, data quality, cost, and drift. • Collaborate with compliance and risk partners for safe AI use. • Partner closely with Product, Engineering, and Data teams. • Build programs to elevate AI fluency across the Claims organization. • Lead pilots and structured experiments to test new agentic patterns and workflows. • Define and track KPIs for human–AI collaboration.

• Develop and execute the AI & Data GTM strategy for Life Sciences clients, with a focus on GenAI, Agentic AI, predictive analytics, and data modernization. • Build a robust pipeline for AI-driven initiatives, including clinical trial analytics, sales effectiveness, patient intelligence, real-world evidence platforms, and intelligent automation for regulatory processes. • Drive commercial excellence by achieving Revenue, Gross Margin, and Net Margin targets for AI & Data engagements. • Engage C-level executives and senior stakeholders to define AI and data transformation roadmaps, including GenAI adoption and agent-based automation. • Consult clients on AI & Analytics solutions, data strategy, AI governance, and responsible AI frameworks. • Identify new opportunities for AI-powered solutions in areas like drug discovery acceleration using GenAI, clinical trial optimization with predictive analytics, and commercial effectiveness across HCPs, Patients, and Payers. • Deliver executive-level presentations showcasing AI-driven business impact. • Translate complex business challenges into AI/ML solution architectures, leveraging Generative AI for scientific literature summarization and molecule design, and Agentic AI for autonomous workflows in clinical operations. • Design end-to-end AI ecosystems integrating data engineering, data science, and visualization platforms. • Drive data modernization programs, including migration to cloud-native data platforms (Snowflake, Databricks, AWS, Azure) and implementation of data governance, lineage, and compliance frameworks. • Champion AI ethics, model explainability, and compliance with FDA/EMA regulations. • Partner with data scientists, ML engineers, and GenAI specialists to deliver high-impact AI solutions. • Collaborate with technology alliances (AWS, Azure, Snowflake, Databricks) to enhance AI solution value. • Build and mentor a high-performing AI & analytics team focused on Life Sciences.