Role Description As a Senior Data Scientist (m/f/d), you will work on exciting projects that deliver first-class solutions powered by modern language models. You will have full command of the technical stack necessary for development and deployment, collaborate closely with stakeholders, and play a key role in shaping the company’s data science strategy. - Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows - Identify opportunities to leverage data for business value and impact - Take ownership of the full technical stack for development and deployment - Design, build, and maintain scalable machine learning models and efficient data pipelines - Ensure robust data management and engineering practices - Collaborate with cross-functional teams to gather requirements and deliver insights - Communicate complex technical concepts clearly to both technical and non-technical stakeholders Qualifications - Master’s or Ph.D. in Data Science, Computer Science, Statistics, or related field or equivalent knowledge and experience - Hands-On experience with Generative AI and Agentic Workflows - Proven experience in taking part in complex projects - Expertise in modern language models and machine learning frameworks - Experience with modern LLM-Supporting Frameworks and Tools - Proficiency in modern LLM Prompting techniques and approaches - Experience with managing feedback training pipelines and fine-tuning - Strong command of programming languages such as Python, R or any strongly-typed computer language - Good knowledge of cloud platforms (AWS, GCP, Azure) and deployment processes Requirements - Familiarity with big data technologies like Spark or Hadoop or any other commercial Data Warehouse and/or Data Lake technologies - Strong background in data architecture and database management - Extensive experience with data management and engineering tools Benefits - Your Workplace: You work fully remote and flexibly from anywhere within Germany. We focus on results—not on where your desk is located. - Teamwork: Our culture is clear, direct, and appreciative. You will be part of a supportive team with flat hierarchies that grows together, even in a remote setting. - Structured Onboarding & Buddy: We won’t leave you hanging, even from afar. Your personal Buddy and our structured onboarding process ensure you find your feet quickly and start your journey well-connected. - Flexible Working Hours: You design your own schedule so that you can be productive while maintaining an optimal work-life balance. - Modern Equipment: You will receive a company laptop and modern technical equipment to ensure your home setup is just as efficient. - Mobility & Sports: Take advantage of Lease a Bike and Eversports to stay fit wherever you work. You’ll also have the chance to participate in our annual team-wide sporting events. - Company Events: Our company and team events take place in Vienna. Remote colleagues are, of course, warmly invited to join us! - The minimum salary for this position is € 65.000,- overpayment possible depending on qualifications

Role Description As a Learning Scientist, Early Numeracy, you will use your expertise in how young children learn mathematics to build models that represent the development of early math knowledge and skills. You will help identify what students learn, how their understanding grows over time, and how different concepts connect and build on one another. A key part of this role is developing ontologies and knowledge graphs that capture student learning progressions and serve as the foundation for product development. You will also design and conduct research studies to evaluate how effectively our products support teaching and learning for students in PreK-5 classrooms. As an Individual Contributor, you will: - Think creatively about applying learning science research within product constraints. - Take a hands-on approach to solving problems. - Communicate complex ideas and research findings clearly to both technical and non-technical audiences. - Work closely with cross-functional teams to ensure learning science insights are translated into meaningful, evidence-based product experiences for students and educators. Qualifications - A PhD in developmental psychology, mathematics education, curriculum and instruction, cognitive psychology, or a related field with a mathematics education focus. - Expertise in education trends in mathematics, such as grade bands (e.g., K-2, middle school) and areas of study (e.g., classroom technology use, personalized learning). - Experience as an early-grades classroom teacher a plus. Requirements - Demonstrates a strong understanding of how students learn and develop mathematical knowledge, including key concepts such as the Standards for Mathematical Practice. - Can clearly explain the progression of learning and the skills students need to be successful in math. - Design and develop math learning progressions and knowledge maps that accurately represent how mathematical understanding and skills build over time. - Distinguishes between educational policies, standards, and the specific skills students need to develop. - Translates standards and learning expectations into clear, measurable student skills and competencies. - Understands how changes in academic standards and educational requirements impact skill development and learning progression. - Experience in applying either qualitative or quantitative methods to educational data. - Familiarity interpreting student performance data. - Proficiency with spreadsheet and productivity software and willingness to learn new tools. - An AI-first approach to work. - Understands business problems and delivers solutions for them. - Communicates clearly and effectively. - Works well with people across different teams. - Takes initiative and can work independently. Benefits - Salary range: 95k – 105k. - Application Deadline: The application window for this position is expected to close on August 10, 2026.

• Support Data Managers with day‑to‑day data management activities, including documentation, data processing, and client data reporting • Export, clean, and review clinical submission files to ensure accuracy, completeness, and compliance before delivery to clients • Evaluate client reconciliation feedback received between data transfers and take appropriate action in accordance with established processes • Perform quality and consistency reviews of study‑specific data outputs by comparing delivered data files against source data and study requirements • Investigate discrepancies, communicate findings to Data Managers and cross‑functional teams, and document results and corrective actions • Assist in the development, maintenance, and preparation of study documentation, including Data Management Plans (DMPs) and Data Transfer Specifications (DTSs) • Coordinate updates to Clinical Data Management task schedules and help ensure deliverables are completed on time • Support tracking and reporting of study metrics, data issues, and file delivery activities • Assist with preparation and formatting of documents, presentations, and templates used by the Clinical Data Management team • Serve as a primary recipient of client reconciliation feedback and ensure investigations and responses are completed within agreed timelines • Maintain accurate, complete, and audit‑ready documentation related to reconciliation activities and data management processes • Support maintenance and storage of study documentation in accordance with company procedures • Contribute to continuous process improvement initiatives and workflow optimization efforts • Assist with CAPA activities and issue resolution related to study‑specific data management activities

Role Description ¡Ven a ser un Zuricher y forma parte de nuestro equipo como Cientifico de Datos! Tu objetivo será desarrollar modelos avanzados analíticos, predictivos, prospectivos que permitan entender, simular y anticipar el comportamiento del negocio y del mercado. Transformar grandes volúmenes de datos en hipótesis, escenarios, modelos y recomendaciones accionables que apoyen la toma de decisiones estratégicas, contribuyendo al crecimiento comercial, captación de mercado, competitividad, eficiencia de la compañía y traducirlos a herramientas de gestión. - Transformar desafíos y oportunidades del negocio en hipótesis, modelos y soluciones analíticas, identificando patrones, relaciones y variables que permitan comprender, explicar y predecir comportamientos relevantes para la organización. - Diseñar, desarrollar y evolucionar modelos analíticos, predictivos y de optimización, incluyendo segmentación, scoring, forecasting y simulación, incorporando nuevas fuentes de información que fortalezcan su capacidad predictiva. - Analizar información interna y externa, para identificar riesgos, oportunidades y tendencias que impacten el crecimiento, la rentabilidad y la sostenibilidad del negocio. - Evaluar, calibrar y monitorear el desempeño de los modelos implementados, garantizando su precisión, estabilidad y generación de valor para la organización. - Desarrollar escenarios prospectivos y simulaciones de negocio que permitan anticipar impactos potenciales y generar recomendaciones accionables para la toma de decisiones. - Impulsar iniciativas de analítica avanzada e inteligencia artificial, comunicando hallazgos y recomendaciones a audiencias técnicas y de negocio, colaborando con todas las áreas para incorporar modelos analíticos en procesos, indicadores y herramientas de gestión. - Documentar metodologías, supuestos, variables, fuentes de información y resultados de los modelos desarrollados, garantizando su trazabilidad, replicabilidad y sostenibilidad en el tiempo. - Colaborar con los equipos de Planeación de Negocio y áreas funcionales para identificar oportunidades de aplicación de modelos analíticos que contribuyan al cumplimiento de los objetivos de crecimiento, rentabilidad y sostenibilidad del negocio. - Ejecutar otras funciones relacionadas con analítica avanzada, modelamiento de datos e inteligencia del negocio asignadas por su People Manager. Qualifications - Profesional en Economía, Informática, Ingeniería Industrial, Matemática, Administración de Empresas, o carreras afines. - Idealmente con formación en data modelling and analytics. Requirements - Dominio de lenguajes como Phyton, SQL, R (opcional). - Conocimiento avanzado en técnicas de IA, Machine Learning. - Conocimiento de Plataformas Nube como Azure, Databricks (opcional). - Experto en herramientas de visualización como Power BI. - 3-4 años de experiencia general. - Experiencia en seguros: SI. - ¿Tiene personas a cargo? NO. - Idioma: Inglés, Nivel: Conversacional. Company Description Imagina trabajar en una empresa que realmente se preocupa por sus colaboradores, clientes, partes interesadas y toda la comunidad involucrada. ¡Imagínate trabajar para una empresa que se compromete con hacer lo correcto y que tiene como objetivo ser el mejor proveedor de seguros del mundo! Zurich es una de las principales compañías de seguros del mundo y una de las pocas que opera a escala global. Con alrededor de 55.000 empleados, dedicados a comprender las necesidades de nuestros clientes y ofrecer soluciones para particulares y empresas, desde pequeñas empresas hasta multinacionales. Aquí, apostamos por la Sostenibilidad, innovando en las políticas de desarrollo y uniéndonos cada vez más con los cambios del mundo. Nos preocupamos por la confianza en la sociedad y en la forma en que estamos constantemente innovando, buscando tecnología y estrategias que nos permitan brindar una experiencia memorable a nuestro cliente. También fomentamos una cultura de diversidad e inclusión. Nuestra declaración de propósito y valores está diseñada para proteger, inspirar confianza y ayudar a nuestros colaboradores a alcanzar su máximo potencial. Por eso, contamos con una política de inclusión laboral que promueve la selección de personas con discapacidad que cumplan con los requisitos de la vacante.