Data Scientist

• Ensure robust and consistent media tracking across all digital platforms
• Support the definition and implementation of global media tracking standards across Paid, Owned, and Earned channels
• Ensure proper setup and maintenance of tracking frameworks (e.g. Supermetrics, GA4, pixels, tagging plans)
• Coordinate tracking implementation across websites, media platforms, and analytics tools
• Validate data collection quality and ensure consistency across markets and platforms
• Support troubleshooting and issue resolution related to tracking and data collection
• Translate business tracking and measurement needs into clear technical requirements
• Work closely with Media teams on business needs
• Work closely with Tech teams to ensure proper implementation of tracking and data flows
• Collaborate with Data Product Managers to align tracking data with data models and data products
• Ensure consistency between tracking setup, data ingestion (e.g. via Supermetrics), and data warehouse structures (BigQuery)
• Monitor and follow up on implementation timelines and deliverables
• Define and enforce data quality checks and validation processes for media data
• Ensure consistency of naming conventions, KPIs, and tracking structures across markets
• Identify gaps or inconsistencies in data collection and drive remediation actions
• Support the Paid Media Data Manager in ensuring data readiness for reporting and analytics
• Ensure tracking enables accurate measurement of campaign performance and optimization
• Contribute to defining measurement frameworks and supporting performance analysis
• Facilitate alignment between media tracking data and reporting tools (e.g. Looker dashboards)
• Coordinate tracking-related projects (that includes AI projects) across business, Tech, and external partners
• Ensure clear documentation of tracking frameworks, requirements, and implementations
• Support communication and alignment with global and local teams
• Contribute to training and upskilling of markets on tracking best practices

Global Media Tracking Data Manager

• Gestión y transformación de bases de datos utilizadas para la estimación y calibración de parámetros de riesgo (PD, LGD y CCF).
• Participación desde la perspectiva de datos de estimación en ejercicios de calibración, backtesting y seguimiento regulatorio.
• Desarrollo de procesos de explotación y tratamiento de información sobre grandes volúmenes de datos.
• Participación en iniciativas de mejora de calidad, consistencia y trazabilidad de la información.
• Uso de herramientas de visualización y reporting para seguimiento y análisis de información de riesgos.
• Colaboración en iniciativas de automatización y transformación apoyadas en IA Generativa y nuevas capacidades analíticas.

• Translate business needs into technical requirements
• Design, develop, and implement statistically grounded methodologies to address business needs
• Debug and problem-solve issues to ensure the delivery of accurate metrics
• Create and document reusable packages and libraries
• Dive into technical problems and figure out solutions that make our product meaningful

Intern Data Scientist – Hybrid

• Design, develop and deploy advanced AI/ML models for telecom use cases such as: Network optimization, Traffic prediction and anomaly detection, QoS/QoE modeling and root cause analysis
• Apply and adapt state-of-the-art AI techniques, including: Deep Learning (CNNs, RNNs, Transformers), Reinforcement Learning for network optimization, Time-series modeling at scale
• Work deeply with real telecom network data (3G/4G/5G), understanding KPIs, counters, and traffic dynamics
• Build production-ready solutions, ensuring scalability, performance, and reliability
• Collaborate closely with data engineers and telecom experts to integrate AI models into real systems
• Act as a technical reference within the team, contributing to best practices and code quality
• Explore and apply Generative AI and LLM-based approaches to telecom use cases

Senior Data Scientist

• Own the customer value narrative: Build and maintain the infrastructure that lets every customer (and our sales team) articulate Verify's ROI in dollars and percentages
• Ship production ML systems: From feature engineering through deployment, monitoring, and iteration
• Create reliable, self-serve data products: Dashboards, APIs, and datasets that scale without manual intervention
• Drive pricing and packaging decisions: Provide the quantitative foundation for how we charge and what we bundle
• Partner across the organization: Work with Product, Engineering, Finance, Sales, and Customer Success to embed data into every decision
• Report to leadership: Own KPI narratives on margin drivers, growth levers, and competitive positioning

• Analizar, preparar y modelar datos de ventas y clientes, identificando patrones y señales tempranas mediante análisis de datos y modelos de Machine Learning/ Inteligencia Artificial que ayuden a anticipar necesidades y mejorar la eficiencia.
• Colaborar en proyectos de IA, concretamente serás el responsable de liderar un proyecto de detección de esquemas eléctricos, y su traducción a una lista de materiales, para esto usarás tecnologías de IA como Computer Vision, LLMs, RAGs......
• Generar insights estratégicos combinando datos de múltiples fuentes para detectar ineficiencias, priorizar acciones y apoyar decisiones clave que optimicen la experiencia del cliente y los procesos internos.
• Comunicar resultados de forma clara, creando visualizaciones aplicando soft skills como pensamiento crítico, trabajo colaborativo y storytelling para asegurar que los equipos comprendan, actúen sobre las conclusiones de los análisis.

Data Science Intern

• Mantener datos de ingeniería de productos de alta calidad en Windchill.
• Soporte y resolución de problemas de integración de Windchill y NX.
• Apoyar la ejecución del cambio mediante la investigación de errores y problemas de flujo de trabajo.
• Documentar, rastrear y dar seguimiento a incidentes y solicitudes; asegurar resolución oportuna y comunicación clara con las partes interesadas.
• Realizar pruebas de validación para actualizaciones de herramientas y contribuir a Implementaciones estables.
• Proporcionar soporte estructurado al usuario y desarrollar mantener materiales de capacitación y guías de mejores prácticas.
• Impulsar la estandarización de prácticas de gestión de datos PLM entre sitios.

Product Life & Data Manager

• Trabajar con lenguajes y librerías de Data Science como Python, Pandas, y TensorFlow
• Implementar modelos de datos y realizar análisis de datos
• Colaborar con equipos para entregar soluciones innovadoras
• Participar en eventos y formaciones internas para el desarrollo profesional

• Define and own the data & AI strategy in close collaboration with the CTO and product leadership.
• Build and lead a high-performing team of 2–4 data engineers, analysts, and ML/AI specialists.
• Act as the internal authority on data and AI, shaping how Abion thinks about and uses these capabilities.
• Design and deliver a scalable, well-governed data platform, including pipelines, warehousing, and data quality.
• Establish data standards, documentation practices, and governance frameworks from day one.
• Partner with Platform Engineering to ensure data is a first-class citizen in Abion’s architecture.
• Identify and prioritise the highest-value AI opportunities across Abion’s product portfolio and internal operations.
• Lead the design and delivery of AI-powered features, working tightly with Product and Platform Engineering.
• Ensure AI applications are robust, explainable, and aligned with Abion’s legal and compliance context.

Head of Data and AI

• Leverage advanced machine learning and robust data engineering techniques
• Collaborate with multidisciplinary teams including toxicologists, researchers, and safety professionals
• Develop predictive models and deliver analytical solutions
• Build scalable data pipelines and transform raw experimental outputs

Principal Data Scientist – R&D DSDH – Preclinical Sciences, Translational Safety

• Leverage advanced machine learning and data engineering techniques to drive impactful decisions
• Create AI-ready datasets, develop predictive models, and deliver analytical solutions
• Collaborate with multidisciplinary teams to promote improved safety evaluations and facilitate translational research

Principal Data Scientist – R&D DSDH, Preclinical Sciences, Translational Safety

• Design, build, and optimize data capture, processing, and storage solutions
• Create and optimize data flows for structured and unstructured data using Python, R, SQL
• Develop and maintain TDS‑specific data repositories
• Partner with data scientists, TDS domain experts, and digital technology teams
• Implement data quality and performance standards
• Engage with scientific, technical, and operations stakeholders to drive adoption

Principal Scientist, Data Science – R&D, Therapeutics Development & Supply

• Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing TDS data from diverse data generation sources and systems.
• Create and optimize data flows for structured and unstructured data using Python, R, SQL, cloud services, and other modern engineering tools.
• Develop and maintain TDS‑specific data repositories, implementing enterprise‑level data models and creating new models as needed.
• Enable AI/ML readiness by ensuring data is well‑structured, versioned, traceable, and semantically aligned with enterprise data standards.
• Partner with data scientists, TDS domain experts, and digital technology teams to translate business needs into high‑quality data products and engineering requirements.
• Engage with scientific, technical, and operations stakeholders to understand requirements, design data solutions, and drive adoption.

Principal Scientist, Data Science – R&D DSDH – Therapeutics Development & Supply

• La persona seleccionada se unirá al COE IFRS9 de Data & Analytics de GRM España, responsable de los parámetros que intervienen en la medición del riesgo de crédito en España para Provisiones.
• El desarrollo de modelos para el cálculo de los parámetros (PD, LGD, CCF, entre otros).
• El mantenimiento de los mismos, realizando ejercicios de backtesting o recalibrando.
• La implantación de nuevas metodologías, o el desarrollo de mejoras sobre las metodologías existentes.
• Coordinación con las unidades Analytics holding para la adecuación de las metodologías en local.
• Dar soporte en las revisiones llevadas a cabo por parte de las distintas capas de control, internas y externas.

Senior Data Scientist – COE IFRS9

• Incorporarse al equipo de Smart Steps, el producto Big Data de Telefónica.
• Colaborar en la explotación de datos y generación de insights de valor.
• Mejorar algoritmos, integración de APIs y análisis de datos en equipo.

Data Scientist – SmartStep

• The Data Scientist role will be part of the Supply Planning Data Intelligence organization and will be responsible for building, training, deploying, and maintaining AI/ML models and automation tools for supply chain master data.
• Acting as part of the "tech engine" of the Intelligent Data Factory initiative, this role develops advanced analytics solutions—such as optimization algorithms, predictive models, generative AI tools, and intelligent data agents—to drive autonomous and self-healing data pipelines.
• Collaborate closely with Data Owners and supply chain subject matter experts to ensure that real-world constraints and business rules are accurately modeled.
• Develop Optimization & Simulation Algorithms: Design, build, and refine algorithms for supply chain planning optimization and scenario simulation.
• Build Predictive Machine Learning Models: Develop and deploy predictive models using supervised and unsupervised machine learning techniques to improve master data-driven decision making.
• Maintain end-to-end data pipelines, ensuring models are regularly retrained and validated with clean, well-labeled data.
• Implement Generative AI & NLP Solutions: Create and integrate generative AI and natural language processing solutions to automate and enhance data management processes.
• Develop Intelligent Data Agents & Automation Bots: Design and deploy AI agents and robotic process automation (RPA) bots to handle repetitive master data tasks and proactively resolve data issues.
• End-to-End Model Deployment & Maintenance: Own the full lifecycle of data science solutions from development to deployment and ongoing maintenance. Monitor model and system performance, troubleshoot issues, and implement improvements or retraining as needed to maintain accuracy and efficiency.
• Drive Innovation & Phased AI Enablement: Contribute to the continuous innovation of the Intelligent Data Factory by staying abreast of cutting-edge AI techniques and identifying opportunities to enhance automation.
• Support a phased delivery approach to AI enablement in master data management.

Senior Manager, Data Scientist – Supply Chain

• AI & Data Science Strategy: Defining and evolving the company’s AI strategy across traditional machine learning, experimentation, evaluation, and generative AI applications.
• Technical Leadership: Acting as the senior technical anchor for the function, ensuring the team applies strong scientific thinking, robust experimentation practices, and sound engineering judgment.
• GenAI Adoption: Identifying where LLMs, agents, and related tooling can materially improve products, workflows, and team leverage, while avoiding hype-driven decisions.
• Ecosystem Building: Creating the environment, tooling patterns, and ways of working that allow teams with mixed seniority to build and operate AI solutions effectively.
• Team Leadership & Development: Coaching and developing emerging leaders and strong individual contributors, while helping define the right long-term organizational structure.
• Cross-functional Translation: Bridging product, engineering, platform, and executive stakeholders to ensure AI initiatives are actionable, aligned, and well-prioritized.
• Organizational Stabilization: Providing the seniority and leadership depth needed during a period of team transition and leadership change.
• Selective Hiring: Helping calibrate and attract senior profiles who combine machine learning depth, strong judgment, and practical exposure to modern GenAI systems.

AI & Data Science Director

• Analizar datos de siniestros para identificar patrones y tendencias.
• Colaborar con los equipos de tramitación de siniestros para la optimización de los procesos.
• Elaboración y actualización de informes y cuadros de mando que sirvan como apoyo en la toma de decisiones (tramitación, proveedores, fraude, etc.).
• Utilizar técnicas de análisis estadístico y herramientas de visualización de datos.
• Desarrollar modelos predictivos que anticipen el comportamiento de los siniestros y optimicen la operativa.
• Participar en la implementación de cambios que incrementen la eficiencia y reduzcan costes.
• Colaboración en proyectos transversales como la elaboración del Plan anual o grupos de trabajo.
• Comunicación efectiva con otros departamentos de la entidad (financiero, organización, suscripción, etc.) para la consecución de logros comunes.
• Elaboración. desarrollo y mantenimiento de los diversos controles internos que permitan la mitigación de riesgos.
• Extracción y documentación de informes para los stakeholders de la Joint Venture.
• Aplicación de las políticas y estándares del Grupo Allianz.

Data Scientist – Claims

• Define and execute JOOR’s analytics strategy, aligning it directly with company goals, product roadmaps, and revenue targets.
• Mentor, and lead the analytics and data engineering team.
• Collaborate with Product and Engineering to integrate analytical models and insights directly into the JOOR platform.
• Oversee the development of executive dashboards, KPI tracking, and automated reporting systems to give stakeholders clear visibility into business health (GMV, user engagement, retention).
• Champion data integrity. Lead the team to define a scalable data architecture, accurate pipelines, and stringent data governance protocols.
• Translate complex data findings into clear, strategic recommendations for non-technical stakeholders.

See all jobs on JobTailor

Global Media Tracking Data Manager

Data Scientist

Intern Data Scientist – Hybrid

Senior Data Scientist

Senior Data Scientist

Data Science Intern

Product Life & Data Manager

Senior Data Scientist

Head of Data and AI

Principal Data Scientist – R&D DSDH – Preclinical Sciences, Translational Safety

Principal Data Scientist – R&D DSDH, Preclinical Sciences, Translational Safety

Principal Scientist, Data Science – R&D, Therapeutics Development & Supply

Principal Scientist, Data Science – R&D DSDH – Therapeutics Development & Supply

Senior Data Scientist – COE IFRS9

Data Scientist – SmartStep

Senior Manager, Data Scientist – Supply Chain

AI & Data Science Director

Data Scientist – Claims

Head of Analytics