Senior Data Scientist

The Role

As a Data Scientist, you will focus on translating advanced AI/ML research into scalable, production-ready solutions that drive business impact for Vanguard. You will collaborate closely with business units, product teams, and stakeholders to design, implement, and deploy data-driven models that optimize processes, enhance client experiences, and support strategic decision-making. This role requires a balance of technical expertise, software engineering rigor, and business acumen to deliver practical, high-quality solutions in real-world financial applications.

Core Responsibilities

• Develop and deploy machine learning models (e.g., time-series forecasting, NLP pipelines, generative AI tools) to solve specific business challenges in finance, such as risk modeling, portfolio optimization, or client personalization
• Partner with cross-functional teams to identify business needs, translate requirements into technical specifications, and validate model performance in production environments
• Optimize existing AI/ML workflows for scalability, efficiency, and reliability using frameworks like PyTorch, TensorFlow, or cloud-based infrastructure
• Collaborate with research scientists to adapt cutting-edge algorithms (e.g., LLM fine-tuning, reinforcement learning) into actionable business solutions
• Document and maintain codebases, ensuring reproducibility, version control, and alignment with industry best practices (e.g., CI/CD pipelines)
• Mentor junior team members and educate stakeholders on AI/ML capabilities, limitations, and ethical considerations

• Education: Master's or PhD in Computer Science, Statistics, Mathematics, Analytics, Economics, or a closely related field. (Graduate degree strongly preferred; equivalent advanced training and experience considered.)
• Experience: Proven hands-on experience in advanced analytics, applied data science, or machine learning engineering, with a proven track record in the financial services industry or similar complex domains
• Technical Mastery: Demonstrated expert proficiency in Python and R, including hands-on experience with leading ML frameworks (Scikit-learn, PyTorch, Keras), data engineering tools (SQL, Spark), and cloud platforms (AWS, Azure, GCP). Deep experience in applied mathematics, statistical modeling, machine learning, and AI applications
• Production Impact: Successfully deployed multiple ML models to production environments, with direct business impact (e.g., measurable improvements in KPIs, cost savings, or risk reduction). Experience with containerization (Docker, Kubernetes), CI/CD, SDLC, and MLOps/observability practices
• Advanced Methods: Expertise in NLP, deep learning, transformer-based models, and generative AI. Proven ability to define and track value metrics, run experimentation (A/B testing, causal inference), and drive stakeholder adoption from MVP through scale
• Domain Knowledge: Familiarity with financial domains such as asset management and risk analytics, with a history of delivering quantifiable business outcomes (e.g., increased revenue, reduced risk, improved operational efficiency)
• Communication & Influence: Exceptional verbal and written communication skills, with the ability to articulate complex data science concepts and technical results to non-technical stakeholders and senior leadership. Experience leading cross-functional teams and driving adoption of analytics solutions
• Leadership: Demonstrated success in mentoring and developing junior talent, leading organization-wide training initiatives, and fostering a culture of innovation and collaboration

• Vanguard is not offering sponsorship for this position
• This is a hybrid position and would require you to work in the office Tuesday-Thursday