Data Scientist - Remote
Sundayy · United States
- Hybrid
- Full-time
- $150,000 / year
- United States
Job highlights
- Lead ML model development and deployment for strategic decisions.
- Work remotely with cross-functional teams on analytical solutions.
- Handle large datasets and design sophisticated algorithms.
- Influence business growth with AI models and insights.
- Drive innovation in data science methods and applications.
About the role
About The Company
Volkswagen Financial Services (VWFS), a wholly-owned subsidiary of Volkswagen Group, is a leading provider of mobility solutions dedicated to supporting its brand partners, including Audi, Ducati, and Volkswagen. The company specializes in offering accessible mobility options through various financial services such as Retail Leasing, Retail Financing, Commercial Financing for both new and used vehicles, and End-of-Term vehicle disposition. With a focus on innovation and customer-centric solutions, VWFS aims to enhance the automotive ownership experience by leveraging advanced financial products and services. The organization is committed to fostering a dynamic and inclusive workplace, emphasizing continuous growth, technological advancement, and sustainable mobility initiatives.
About The Role
The Staff Data Scientist at Volkswagen Financial Services plays a pivotal role within the Data Science team, responsible for leading the development, implementation, and deployment of machine learning models that drive strategic business decisions. This is a remote, career-level position designed for an experienced professional with a strong background in data science and machine learning. The role involves working closely with cross-functional teams, including product management, business stakeholders, and leadership, to translate complex business problems into impactful analytical solutions. The ideal candidate will have extensive experience in handling large data sources, designing sophisticated algorithms, and deploying scalable AI models that influence operational and strategic outcomes. This position offers an excellent opportunity to contribute to innovative projects, influence business growth, and advance the company's data-driven culture.
Qualifications
- Bachelor's degree in Computer Science, Statistics, Economics, Engineering, Operations Research, or a related quantitative field
- 10+ years of professional work experience in data science or related fields
- At least 5 years of hands-on experience in data science, including developing and deploying machine learning models
- Proven expertise in algorithm tuning, model validation, and back-testing
- Extensive experience in extracting, curating, exploring, and analyzing large datasets
- Strong background in integrating machine learning solutions into business processes
- Excellent knowledge of machine learning models and analytical tools
- Ability to communicate complex data insights clearly to non-technical stakeholders
- Experience with A/B testing, causal analysis, and model evaluation
- Passion for innovative problem solving and data-driven decision making
Responsibilities
- Extract, curate, explore, and analyze data from large and complex data sources to identify patterns and insights (30%)
- Develop, deploy, and maintain AI and machine learning models that support business objectives (30%)
- Collaborate with stakeholders, product managers, and leadership teams to translate business requirements into practical analytical solutions (20%)
- Introduce and advocate for new machine learning methods, driving innovation and change within the organization (5%)
- Research new data sources, analytical tools, and contribute to the development of new applications and data quality initiatives (5%)
- Provide ongoing support to business units by delivering insights, reports, and recommendations (10%)
Benefits
- Eligibility for annual performance bonus
- Comprehensive healthcare benefits
- 401(k) retirement plan with company match
- Defined contribution retirement program
- Tuition reimbursement for continued education
- Company lease car program
- Paid time off and holidays
Equal Opportunity
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 characteristic protected by applicable laws. We are committed to fostering an inclusive environment where diversity is valued and all individuals have the opportunity to succeed. This role description is a general guideline and does not constitute a contractual obligation. The company participates in E-Verify, maintains a drug-free workplace, and performs pre-employment substance abuse testing.
Key skills/competency
- Data Science
- Machine Learning
- AI Model Deployment
- Data Analysis
- Algorithm Tuning
- Model Validation
- A/B Testing
- Causal Analysis
- Quantitative Analysis
- Stakeholder Communication
Skills & topics
- Data Scientist
- Machine Learning
- AI
- Data Analysis
- Algorithm Tuning
- Model Deployment
- Quantitative Analysis
- Volkswagen Financial Services
- Remote
- Staff Level
How to get hired
- Tailor your resume: Highlight your 10+ years of data science experience, 5+ years in ML model development, and success in algorithm tuning and validation.
- Showcase impact: Quantify your achievements in data analysis, model deployment, and influencing business decisions using specific examples.
- Prepare for technical interviews: Brush up on ML concepts, algorithm tuning, model validation, A/B testing, and causal analysis.
- Demonstrate communication skills: Be ready to explain complex data insights clearly to non-technical stakeholders.
- Research VWFS: Understand their focus on mobility solutions and financial services to align your application with their goals.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities of a Staff Data Scientist at Volkswagen Financial Services?
- As a Staff Data Scientist at Volkswagen Financial Services, you will lead the development and deployment of machine learning models, analyze large datasets, collaborate with stakeholders to translate business needs into analytical solutions, and drive innovation in data science methods. You'll also provide ongoing insights and recommendations to business units.
- What qualifications are essential for the Staff Data Scientist role at VWFS?
- Essential qualifications include a Bachelor's degree in a quantitative field, 10+ years of professional experience in data science, and at least 5 years of hands-on experience developing and deploying machine learning models. Expertise in algorithm tuning, model validation, analyzing large datasets, and communicating complex insights is also crucial.
- Is the Staff Data Scientist position at Volkswagen Financial Services remote?
- Yes, the Staff Data Scientist position at Volkswagen Financial Services is a remote role, offering flexibility to work from anywhere.
- What kind of benefits does Volkswagen Financial Services offer its employees?
- VWFS offers a comprehensive benefits package including an annual performance bonus, healthcare benefits, a 401(k) with company match, tuition reimbursement, a company lease car program, and paid time off.
- How does Volkswagen Financial Services support diversity and inclusion?
- Volkswagen Financial Services is an Equal Opportunity Employer committed to fostering an inclusive environment. They value diversity and encourage applicants from all backgrounds, prohibiting discrimination based on protected characteristics.
- What is the expected experience level for the Staff Data Scientist role?
- This is a career-level position requiring significant experience. Candidates should have over 10 years of professional work experience in data science, with at least 5 years focused on developing and deploying machine learning models.
- How can I best prepare for a Staff Data Scientist interview at Volkswagen Financial Services?
- To prepare for an interview, focus on showcasing your experience with machine learning model development, deployment, algorithm tuning, and validation. Be ready to discuss your approach to analyzing large datasets and how you communicate complex data insights to non-technical audiences. Familiarize yourself with VWFS's business and how data science contributes to their mobility solutions.