Forward Deployed Data Analyst
Electric Twin
IT, Data Science
Posted on Mar 19, 2026
Role
Who you are
- Quantitative degree (mathematics, statistics, economics, physics, computer science, psychology, or related field)
- 2-5 years in data analysis, market research, consulting, or customer-facing technical roles
- Excellence at translating complex technical concepts for non-technical executives
- Proven ability to manage sophisticated customer relationships independently
- Thrives in ambiguous, fast-moving startup environments
- Proficient in Python
- Quick learner who can master new AI/ML platforms and concepts
- Be able to identify root cause of technical issues in data and evaluation pipelines
- High levels of self-discipline and organisation
- Intellectually curious with exceptional attention to detail
- Builds trust quickly with senior stakeholders
- Comfortable with high-stakes decisions and broad responsibilities
- Strong ownership mentality with composure under pressure
Desirable
- Experience with LLMs, AI systems, or enterprise SaaS implementations
- Management consulting background, especially in technology transformation
- Track record presenting to C-suite executives
- Knowledge of behavioural science or consumer insights
What the job involves
- As a Forward Deployed Analyst, you'll be the critical bridge between our AI platform and the end user. Working directly with clients, you'll configure synthetic populations that mirror their real-world audiences and help them extract maximum value from behavioural insights
- This high-impact, customer-facing technical role operates at the intersection of AI, data science, and strategic consulting - ideal for someone with a quantitative/data science background looking to move into AI products
- Transform Datasets to Onboard onto our Product: Design synthetic population queries by onboarding custom datasets for customers
- Improve Data Pipelines: Diagnose data issues and partner with engineering to enhance platform capabilities
- Build confidence through rigour: Evaluate synthetic methodologies using established validation frameworks to build client trust in AI insights for high-stakes decisions
- Lead technical engagements: Own the technical dialogue with customers—understand their data, design optimal solutions, and implement them collaboratively
- Scale adoption: Enable customers to unlock full product value across the whole organisation through effective training, documentation, and use case storytelling
- Shape our product: Represent the voice of the customer - gather field feedback and inform product priorities based on real implementation patterns
Salary benchmarks
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