• Own the architecture and reliability of the UA data pipeline — BigQuery, dbt, Jenkins, AppsFlyer/SKAN attribution, and our downstream dashboards and Mixpanel warehouse sync • Drive the migration of remaining Python transformation scripts into dbt; establish CI/CD, testing standards, and dev/prod environment hygiene • Partner with engineering on the ingestion layer (ad platform APIs, Firebase, custom subscription backend webhooks) and upstream data quality • Evaluate and introduce new tooling when it's clearly the right call; default to keeping the stack simple • Own the definitions, logic, and reliability of our core metrics: installs, trials, trial-to-paid, RPP, ROAS, CAC, LTV, churn • Lead our attribution methodology — MMP (AppsFlyer), SKAN 4, SSOT deduplication — and translate it clearly to the UA and executive teams • Support our experimentation program: help PMs and the UA team design tests, validate results, and build statistical muscle across the org • Experience building or managing experimentation infrastructure (A/B testing platforms, statistical significance frameworks) • Build self-service data products that reduce the number of ad hoc requests hitting the team — including AI-powered tooling (e.g. natural language querying over Mixpanel/BigQuery, automated anomaly detection, LLM-assisted reporting) where it delivers real leverage • Own product analytics instrumentation strategy in partnership with engineering — event taxonomy, Mixpanel governance, Firebase event schema • Translate product analytics into actionable insight for PMs: retention curves, funnel analysis, feature adoption, onboarding optimization • Ensure the product team can answer their own questions without always needing the data team in the loop • Manage and develop two data scientists; make hiring decisions around expansion of the team as needed • Partner closely with the UA Manager, Growth PM, and Head of Product as the data team's primary business-facing contact • Set sprint cadence, manage the data backlog, and keep the team focused on high-leverage work • Drive data governance and data semantic layer development; make our visualization platform more usable for non-technical stakeholders • Help the organization identify and automate high-friction internal workflows using AI — this is a company-wide priority with executive sponsorship • Champion a culture of practical AI adoption on the data team and beyond

• Lead full lifecycle project management from data setup to database lock • Ensure successful delivery of CDM activities to time, budget, and regulatory standards (ICH-GCP) • Act as the primary liaison for clients—managing communication, escalations, and expectations • Drive operational excellence, process consistency, and team productivity across global CDM projects • Manage budgets, scope changes, risk mitigation, and resource allocation • Represent Quanticate at client meetings, audits, and conferences • Assist on bid defences with clients.

• Own the analytical work supporting ClassDojo's district growth • Work directly with Sales, Marketing, and Product leadership to build systems and find insights • Build single reliable reporting model integrating multiple data sources • Identify key drivers of pipeline conversion and build predictive models • Clean and structure fragmented data into stable analytical models • Collaborate with District GTM leadership on key business questions

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.