• Translate business problems into hypotheses and perform exploratory data analysis. • Participate in building and evaluating machine learning models. • Develop scripts and simple pipelines for data processing and analysis. • Collaborate with data engineers, clinical teams, and business areas. • Document learnings and ensure code is well organized. • Contribute to dashboards and reports to communicate results.

Role Description This position is Career Level 30P Home Based with a Role Classification of Fully Remote. The role resides within VWFS’s Data Science & AI CoE team and focuses on end-to-end model development. It requires a proven track record of successful model development and quantifiable business impact. It is not primarily a data analytics or ML engineering role. The Principal Data Scientist will lead high-impact initiatives that directly contribute to VWFS’s stated goal to become a data and AI-driven organization. Potential projects cover the entire spectrum of automotive finance, from automated decision-making to fraud detection and business process improvement. Responsibilities within this Role - Lead data science product development, set standards, best practices, and innovation for the data science CoE (25%) - Experimentation, build, integration of data science solutions into core business processes and new opportunities (75%) - Definition and ongoing improvement of a machine learning environment - Develop and deploy AI models that impact business decisions - Establish best practices and governance routines to ensure adherence to model management policies, peer reviews, and compliance to our policy standards for privacy, ethics, and bias. - Bring relevant data science techniques, algorithms, and tools to your team - Provide technical oversight, help and mentorship to the junior data scientists on the team - Apply suitable techniques for model testing and tuning, to assess accuracy, fit, validity, and robustness - Innovate new ML methods in the data science space and drive change throughout the business - Contributes to code documentation, maintains playbooks, and provides timely progress updates - Help generate compelling hypotheses to drive new business creation Qualifications - Bachelor’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field - Master’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field Requirements - 12+ years of data & analytics work experience with 8+ years in data science - 7+ years in utilizing methods and tools to extract, curate, explore, and analyze data from large data sources - 7+ years in developing, integrating and deploying machine learning solutions into the business decision making process - 7+ years in leveraging algorithms, tune parameters and back testing validation - 5+ years leading ML project development 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, including both traditional ML and GenAI - Utilize a consultative approach to work with the business to solve challenging problems using various analytical techniques - Embrace, research, explore, and enable new quantitative techniques and technologies in data science that will help define VWFS as an industry leader in the application of data science techniques - Extensive experience with model evaluation and solid grasp of A/B testing and causal analysis - Research new data sources and analytical tools, contribute to new application development, and data quality improvement efforts - Ability to originate curiosity to collaborate with different business units to co-create solutions - Passion for data analysis and problem solving - Establishes and maintains effective performance tracking; identifies improvement opportunity, form hypothesis, propose, design and implement tests to drive strategy enhancement and optimization. - Superior ability to communicate technical ideas and results to non-technical users in written and verbal form Company Description 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.

Role Description We are seeking a talented individual to join our team as a data professional who will harness the power of data to drive decision-making and innovation. This position offers the flexibility of working remotely while contributing to meaningful projects that impact our clients and the wider community. - Analyse large datasets to derive actionable insights and support strategic initiatives. - Develop and implement predictive models and machine learning algorithms. - Collaborate with cross-functional teams to identify opportunities for leveraging data. - Communicate findings and recommendations to stakeholders in a clear and concise manner. - Continuously monitor and improve existing data processes and systems. Qualifications - Proven experience in data science or a related field. - Proficiency in programming languages such as Python or R. - Strong understanding of statistical methods and machine learning techniques. - Experience with data visualisation tools such as Tableau or Power BI. - Excellent problem-solving skills and attention to detail. Requirements - Experience with big data technologies such as Hadoop or Spark. - Familiarity with cloud platforms like AWS or Azure. - Strong communication skills and the ability to work collaboratively in a remote environment. Benefits - Salary: 40000 - 149997 USD Per annum

• Desenvolver modelos de machine learning, análises estatísticas e soluções de dados que apoiem a tomada de decisão. • Trabalhar próximo aos times de negócios e engenharia para entregar valor por meio de análises e modelos confiáveis. • Desenvolver e treinar modelos de machine learning (classificação, regressão, clusterização, séries temporais); • Realizar análises exploratórias de dados, limpeza, transformação e preparação de datasets; • Criar protótipos de modelos e documentar hipóteses, experimentos e resultados; • Preparar e automatizar pipelines de coleta e tratamento de dados com Engenharia de Dados; • Realizar validação estatística, tuning de hiperparâmetros e testes A/B; • Apoiar equipes de produto e negócio com insights baseados em dados; • Construir dashboards e análises em ferramentas como Power BI, Tableau ou Looker; • Utilizar boas práticas de versionamento de código e documentação; • Garantir qualidade dos dados e consistência dos modelos aplicados; • Participar de comunidades internas de dados, compartilhando aprendizados e boas práticas.