• Design, develop and refine machine learning models ranging from linear and logistic regression through to tree-based methods, ensemble approaches and advanced algorithms. • Develop proof of concepts and translate exploratory insights into structured modelling approaches. • Design and execute statistical offline simulations to validate modelling approaches prior to live experimentation. • Plan, implement and analyse controlled A/B tests, ensuring statistical robustness and clear interpretation of results. • Define success metrics aligned to business objectives and ensure appropriate evaluation frameworks are in place. • Analyse model performance using appropriate metrics such as precision, recall, ROC-AUC, log loss, calibration measures and model-specific metrics. • Identify potential sources of bias, data leakage and experimental confounding, and proactively mitigate associated risks. • Work closely with Product, Engineering and other stakeholders to prioritise opportunities and ensure models deliver measurable value. • Communicate complex modelling concepts, trade-offs and experimental results in a clear and accessible way to both technical and non-technical audiences. • Contribute to raising the overall standard of modelling practices within the team.

Requisition ID: 65761 Title: Marketing Data Scientist I Main Objective: The Marketing Data Scientist works with Marketing Operations, Data & Analytics Center of Excellence, Product Management, and other stakeholders to enable data-driven marketing by leveraging analytics, predictive modeling, and data visualization to uncover customer insights, optimize campaign performance, and guide strategic decision-making across the organization. Essential Duties and Responsibilities: - Collect, integrate, and clean marketing data from multiple sources (CRM, web analytics, social media, email, etc.) - Ensure data quality, consistency, and usability for analysis - Conduct exploratory data analysis and assist in simple model development. - Analyze campaign, customer, and channel data to uncover patterns, trends, and anomalies - Translate raw data into meaningful insights that inform marketing tactics and strategy - Build, validate, and apply statistical or machine learning models for audience segmentation, lead scoring, predicting traffic patterns and user demand - Evaluate marketing effectiveness using attribution models, A/B tests, and key performance indicators (KPIs) - Create dashboards, reports, and presentations to communicate findings in a clear and actionable way - Partner with internal marketing teams, sales, finance, and data engineering teams to align marketing analytics work with business goals - Leverage modern tools and platforms such as Python, SQL, Databricks, Tableau/Power BI - Adhere to data privacy regulations (e.g., GDPR, CCPA) and organizational standards for ethical data use - Contribute to data stewardship and governance for marketing data assets - Stay updated with industry trends, tools, and best practices in data analytics, digital marketing, and data warehousing. - Continuously expand skillset in data analysis, statistical modeling, and data visualization. - Collaborate with marketing teams, IT, and other departments to gather data requirements and share insights. - Clearly communicate findings and recommendations to both technical and non-technical stakeholders. - Occasional travel for training, meetings, or trade shows may be required Knowledge: Understands digital campaigns, customer data, and KPIs. Familiar with Databricks, SQL, Python, and marketing databases. Shares insights via dashboards, reports, and Databricks visualizations Problem Solving: Solve routine problems of limited scope and complexity following established policies and procedures. Discretion/Latitude: Work is closely supervised. Follow specific, detailed instructions. Education/Experience: Bachelor’s degree preferred. In the absence of a degree, applicants will be considered with a High school diploma or equivalent and 1–2 years of demonstrated experience in data analytics and exposure to machine learning concepts, plus completion of industry‑recognized certifications (PowerBI, Google Analytics, AI etc.) Specialized Skills: Strong communication (written and oral) and presentation skills Business/Customer service orientation. Knowledge in Python and SQL is required. Experience with Power BI, Tableau, or Databricks visualizations is preferred. Arthrex Benefits - Medical, Dental and Vision Insurance - Company-Provided Life Insurance - Voluntary Life Insurance - Flexible Spending Account (FSA) - Supplemental Insurance Plans (Accident, Cancer, Hospital, Critical Illness) - Matching 401(k) Retirement Plan - Annual Bonus - Wellness Incentive Program - Free Onsite Medical Clinics - Free Onsite Lunch - Tuition Reimbursement Program - Trip of a Lifetime - Paid Parental Leave - Paid Time Off - Volunteer PTO - Employee Assistance Provider (EAP) All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other status protected by law.

Job Description Capgemini Engineering, líder mundial en servicios de ingeniería, reúne a equipos de ingenieros/as, científicos/as y desarrolladores/as para ayudar a las compañías más innovadoras a liberar su potencial y construir un futuro mejor. Únete al equipo y continúa tu carrera en una compañía con oportunidades reales de crecimiento, donde puedes marcar la diferencia y donde ningún día es igual al anterior. Estamos buscando perfiles con experiencia en Inteligencia Artificial, Machine Learning y Data para incorporarse a un proyecto internacional con sede en Málaga pero con opción real de trabajo remoto. Se requiere capacidad para desenvolverse con soltura en proyectos de IA aplicada, análisis avanzado y modelado. Funciones principales - Participar en el diseño y desarrollo de soluciones basadas en Machine Learning y analítica avanzada. - Aplicar técnicas de Inteligencia Artificial para resolver problemas complejos sobre grandes volúmenes de datos. - Preparar, limpiar y transformar datos, asegurando calidad, consistencia y trazabilidad. - Construir y optimizar pipelines de datos que alimenten modelos o flujos analíticos. - Experimentar con modelos, evaluar resultados y documentar el ciclo de vida de las soluciones. - Integrarse en equipos multidisciplinares colaborando con perfiles técnicos y funcionales. - Trabajar en entornos ágiles manteniendo buenas prácticas de versionado y documentación. - Participar en proyectos de innovación y adoptar nuevas herramientas/tecnologías cuando sea necesario. Requisitos necesarios - Experiencia laboral previa trabajando con Machine Learning, Inteligencia Artificial o análisis de datos aplicado. - Conocimientos sólidos en Python y librerías de análisis (pandas, NumPy) o ML (scikit‑learn, TensorFlow, PyTorch). - Experiencia manipulando y modelando datos, ya sea en entornos cloud o locales. - Capacidad para desenvolverse con soltura en proyectos de IA, incluso sin un número específico de años. - Inglés mínimo B2 (no es necesario certificado). Se valorará - Experiencia previa con LLMs, RAG, agentes o frameworks de GenAI. - Uso de herramientas cloud (Azure, AWS o GCP). - Experiencia con bases de datos SQL/NoSQL. - Conocimientos de MLOps (Docker, MLflow, CI/CD). - Background en tratamiento de datos para entornos productivos o industriales. - Conocimientos en Spark, PySpark o Databricks. Qué ofrecemos - Contrato con Capgemini Engineering. - Participación en proyectos innovadores dentro del ámbito Aeroespacial / Space – Offshore. - Oportunidad de crecimiento profesional en áreas de IA aplicada y Data. - Modalidades de trabajo flexibles, incluyendo trabajo remoto. - Acceso a formación continua, certificaciones y tecnologías punteras. - Cultura orientada a resultados y aprendizaje continuo. Sobre Capgemini Capgemini es líder global en transformar y gestionar negocios aprovechando todo el poder de la tecnología. Nuestra misión es construir un futuro inclusivo y sostenible. Con más de 360.000 profesionales en más de 50 países, acompañamos a nuestros clientes desde la estrategia hasta la operación, impulsando soluciones de nube, datos, IA, conectividad y software. MAKE IT REAL. ¡Únete al equipo! www.capgemini.com/es-es #LI-VW1 Job Description - Grade Specific The primary focus is to help organizations design, develop, and optimize their data infrastructure and systems. They help organizations enhance data processes, and leverage data effectively to drive business outcomes.

• Формування та експертна валідація структури курсу • Визначення та опис навчальних цілей модулів і контентних одиниць • Створення та ревʼю навчального контенту: скриптів для відео, відеоматеріалів, практичних завдань, портфоліо-проєктів для студентів • Головне завдання - щоб курс готував студентів до реальних задач Junior Product Analyst