Data Scientist, Senior Specialist

Hybrid flexibility in Dallas paired with an embedded technical leadership role. At Vanguard, you will help shape enterprise conversational AI by guiding both traditional and agentic AI/ML work across voice, chat, and emerging agentic experiences. You will own the AI lifecycle end-to-end, from problem formulation through evaluation, deployment readiness, production measurement, and continuous optimization.

Responsibilities

• Lead traditional and agentic AI/ML capabilities that support enterprise conversational AI across voice, chat, and emerging agentic experiences, providing technical direction from design through production.
• Drive Data Science across the full AI lifecycle, including research and experimentation, solution design and development, evaluation, deployment readiness, production measurement, and continuous optimization.
• Develop and optimize models and systems spanning supervised and unsupervised learning, NLP, Generative AI, LLM-based applications, agentic systems, classification models, and knowledge or retrieval-based solutions.
• Advance evaluation and production intelligence for conversational AI by establishing rigorous methods to assess functional accuracy, user-need fulfillment, reliability, and other system-level behaviors.
• Build scalable evaluation approaches that help teams identify failure modes, compare solutions, establish benchmarks, and make evidence-based release decisions.
• Apply analytical and statistical thinking to analyze large datasets, diagnose model and system behavior, conduct root-cause analysis, design experiments, quantify uncertainty, and translate findings into actionable product and engineering recommendations.
• Transform complex data into clear, cohesive stories and diagnostic metrics through exploratory analysis, visualization, statistical reasoning, and business context.
• Partner closely with Product, Engineering, Architecture, UX, Analytics, Risk, and other stakeholders as an embedded technical leader, translating ambiguous business and client needs into measurable Data Science problems and scalable AI solutions.
• Set technical standards and best practices for model development, experimentation, evaluation, validation, observability, explainability, documentation, and responsible use of AI.
• Enable continuous improvement by converting evaluation and production signals into hypotheses, experiments, and model or prompt or system improvements with measurable outcomes.
• Communicate complex AI/ML concepts, risks, and recommendations to technical and non-technical stakeholders, influencing decisions across cross-functional teams.
• Stay current with advances in AI and Data Science and evaluate emerging methods, models, frameworks, and architectures.

Requirements

• 10+ years of relevant Data Science, Machine Learning, or applied AI experience, including leading complex technical work; prior people leadership or technical team leadership is strongly preferred.
• Strong practical foundation in machine learning, including supervised and unsupervised learning, feature engineering, model development, validation, experimentation, and performance measurement.
• Demonstrated expertise in Natural Language Processing and Generative AI, including transformer architectures, embeddings, LLMs, prompting, retrieval-augmented generation, and modern language-model development patterns.
• Hands-on experience designing, building, evaluating, or optimizing agentic AI systems, including orchestration or routing, tool use, knowledge retrieval, multi-turn conversational behavior, and agent evaluation.
• Strong Python and data analysis skills, with experience working with large datasets and using modern ML or Data Science libraries and development environments.
• Experience with AI/ML evaluation and observability, including developing evaluation datasets, metrics, benchmarks, automated evaluations, production monitoring, failure analysis, and connecting model or system behavior to client or business outcomes.
• Ability to balance technical depth with business context, translating loosely defined problems into hypotheses, analytical approaches, measurable success criteria, and actionable recommendations.
• Demonstrated ability to lead and develop Data Scientists, provide technical review, establish engineering and modeling standards, manage competing priorities, and create an environment of accountability, learning, and experimentation.
• Strong data analytics, visualization, and storytelling skills to turn complex data into actionable insights.
• Strong communication and stakeholder-management skills, including the ability to explain complex AI concepts and influence Product, Engineering, Architecture, Analytics, Risk, and senior business stakeholders.

Technologies

• Python
• Transformer architectures
• Embeddings
• LLMs
• Retrieval-augmented generation

Education

Undergraduate degree in Computer Science, Engineering, Data Science, Statistics, Applied Mathematics, Economics, or a related field. Advanced degree preferred.

Working Model and Location

Dallas, TX (hybrid). Vanguard has implemented a hybrid working model for the majority of crew members, designed to combine enhanced flexibility with in-person learning, collaboration, and connection.

Visa sponsorship: Vanguard is not offering visa sponsorship for this position.