Volkswagen Financial Services, a wholly-owned subsidiary of Volkswagen Group, is the trusted key to mobility for its brand partners. We are committed to supporting the Audi, Ducati, and Volkswagen brands and their Dealers, specializing in providing accessible mobility solutions for its Customers. The company’s offerings include Retail Leasing, Retail Financing, Commercial Financing for new and used vehicles, and End-of-Term vehicle disposition. Brief Role Description This position is Career Level 29P, home based with a Role Classification of Fully Remote. Role Summary The Staff Data Scientist role resides within VWFS’s Data Science team and is a key player in planning, executing, and delivering machine learning-based projects. The Staff Data Scientist is responsible for the use of machine learning techniques applied to complex data structures. Critical success factors include the ability to structure problems, develop ML solutions for given problems that eventually see production deployment, and engaging business stakeholders throughout the process. The successful candidate will be a collaborator who is skilled in bringing insights from data to life. The Staff Data Scientist is responsible for helping to structure projects and shepherding them from the ideation and concept phases to eventual production deployment. Responsibilities within this Role • Extract, curate, explore, and analyze data from large data sources (30%) • Develop and deploy AI models that influence business decisions (30%) • Collaborate with stakeholders, product management, and leadership to methodically transform business problems into detailed and practical analytical requirements (20%) • Introduce new ML methods and drive change throughout the business (5%) • Research new data sources and analytical tools; contribute to new application development and data quality improvement efforts (5%) • Provide general business support (10%) Qualification requirements Required Education: • Bachelor’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field Relevant Experience: • 10+ years of work experience • 5+ years of work experience in data science • 5+ years leveraging algorithms, tune parameters and back testing validation • 5+ years in utilizing methods and tools to extract, curate, explore, and analyze data from large data sources • 5+ years in developing, integrating and deploying machine learning solutions into the business decision-making process Skills: • Collaborate with product owners and product managers to translate business requirements into impactful AI solutions that scale • Build, integrate and deploy machine learning solutions into the business decision-making process • Thorough knowledge of machine learning models • Ability to generate and communicate data-driven insights to help guide key business decisions • Eagerness to interact with stakeholders to solve existing business problems and uncover new AI opportunities • Extensive experience with model evaluation and solid grasp of A/B testing and causal analysis • Generate data-driven insights to help guide key business decisions • Research new data sources and analytical tools, contribute to new application development, and data quality improvement efforts • Blend of strategic and tactical thinking, creative and analytic reasoning • Passion for data analysis and problem solving. Volkswagen Financial Services is an Equal Opportunity Employer. We welcome and encourage applicants from all backgrounds, and do not discriminate based on race, sex, age, disability, sexual orientation, national origin, religion, color, gender identity/expression, marital status, veteran status, or any other characteristics protected by applicable laws. This role description is a guideline and does not create contractual rights between the Company and any of its applicants. The Company does not enter into any type of employment contract, implied or written, with its applicants regarding job security. This Organization participates in E-Verify. We maintain a drug free workplace and perform pre-employment substance abuse testing.

• A partir da personalidade de cada aluno e do seu desempenho pedagógico, a Max.ia atua para recomendar intervenções de aprendizagem com alto grau de personalização • Iniciando com a oferta de conteúdos didáticos com a mídia de aprendizagem adaptada para cada perfil para resolver as falhas de aprendizagem que cada jovem e criança têm alta probabilidade de corrigir.

• Collaborate with stakeholders to understand business problems and translate them into data-driven problem statements. • Leverage Large Language Models (LLMs) to generate features from unstructured data (e.g., text) to enhance machine learning models. • Write and optimize SQL queries to manipulate, clean, and analyze structured data from various databases. • Use basic coding skills (e.g., Python) to handle data preprocessing, transformation, and running ML models independently. • Develop, train, and evaluate machine learning models, ensuring the correct model is selected for each problem. • Perform model validation, fine-tuning, and feature engineering to optimize performance • Communicate complex analytical findings in clear, concise ways to both technical and non-technical stakeholders. • Stay updated with the latest developments in LLMs, ML, and AI technologies to incorporate new techniques into solutions.

• Lead and develop a high-performing Data Science and Analytics Engineering team • Drive data-led product improvements across growth, engagement, and monetization • Partner closely with Product, Engineering, and Leadership to shape strategy • Build systems and frameworks that improve decision speed and clarity • Establish clear and trusted metrics and data definitions • Integrate AI into data workflows to improve efficiency and insight generation • Maintain a high hiring bar and strong team culture