VanguardData Scientist, Specialist
AI in this role
Core Responsibilities
Build and enhance AI-powered Digital Twins that simulate customer behavior, preferences, and decision-making.
Lead analytic and AI initiatives that improve simulation fidelity, business relevance, and predictive accuracy through experimentation, validation, and real-world outcome measurement.
Apply behavioral science, customer research, UX insights, and marketing analytics to develop and refine human-centered AI models.
Develop and optimize LLM, RAG, and agentic AI solutions, including data preparation, evaluation frameworks, prompt engineering, and model performance measurement.
Partner with Product, Marketing, Analytics, UX Research, and Technology teams to translate business problems into scalable AI and data science solutions. Communicate findings and recommendations to stakeholders and mentor junior data scientists and analysts.
Qualifications
RequiredMinimum five years of experience in Data Science, Analytics, Machine Learning, Marketing Analytics, or a related quantitative field.
Demonstrated strength in at least one of the following areas: Analytics: Deep problem-solving experience in marketing, customer behavior, UX research, survey analysis, experimentation, behavioral science, or related domains.
Applied AI / Data Science: Experience building solutions using LLMs, agentic systems, prompt engineering, model fine-tuning, RAG architectures, and AI evaluation frameworks.
Strong programming skills in Python and SQL, along with a solid foundation in statistics, machine learning, and experimental design.
Strong communication skills with the ability to translate complex analytical findings into actionable business recommendations.
PreferredExperience developing AI systems that model, simulate, or predict human behavior, preferences, or decision-making.
Experience building Digital Twins, synthetic personas, synthetic customers, or similar human simulation capabilities.
Experience measuring alignment between AI predictions and real-world outcomes and improving model performance through experimentation and validation.
Advanced degree in Data Science, Statistics, Applied Mathematics, Economics, Computer Science, Behavioral Science, Psychology, or a related field.
Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
How we rate this
Data Scientist, Specialist at Vanguard rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, RAG, Fine Tuning, and AI Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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