About Electric Twin
Most organisations make their biggest decisions on a thin slice of evidence — a handful of customer calls, one survey, instinct when the data runs out. Electric Twin changes that. We're a behavioural simulation platform that lets organisations test ideas, messages, and decisions against synthetic populations — digital twins of real audiences — and get answers in minutes that would otherwise take weeks.
The work is grounded, and the engineering is real. We've run over 40,000 evaluations across populations covering 155 countries. Independent academic research with Professor Michael Muthukrishna at the LSE found our outputs come back roughly 10,000× faster than traditional methods, at 95% accuracy. AI is part of what we build, but it isn't the product. The hard work is system design, data, orchestration, and making outputs trustworthy enough that people act on them. Running population-scale simulations is a systems problem as much as a science one — foundation models, behavioural data, evaluation pipelines, and the infrastructure that holds them together, with real engineering problems at every layer.
How the work gets done here isn't handed down — it's worked out by the people closest to it. You'd help shape what gets built or sold and why, decide where the trade-offs sit between speed and depth, and judge when something is ready for customers and when it needs another pass. What the role involves day-to-day, what your first six months look like, and how compensation, equity, growth and flexible working are structured are all set out in detail below — the headline is that early joiners get meaningful equity, a clear path to grow with the company, and the flexibility to work around the rest of your life.
Electric Twin was founded by Dr Ben Warner (former Chief Data Advisor to the UK Prime Minister) and our CEO, Alex Cooper (a former senior military commander and Director of Mass Covid Testing in the pandemic). We're backed by top tier investors including Atomico, LocalGlobe, Mercuri, and angels including Marc Andreessen. We have a high-class team of engineers, AI researchers, behavioural scientists, and operators — careful with the science, careful with the responsibility."
About Electric Twin
Most organisations make their biggest decisions on a thin slice of evidence — a handful of customer calls, one survey, instinct when the data runs out. Electric Twin changes that. We're a behavioural simulation platform that lets organisations test ideas, messages, and decisions against synthetic populations — digital twins of real audiences — and get answers in minutes that would otherwise take weeks.
The work is grounded, and the engineering is real. We've run over 40,000 evaluations across populations covering 155 countries. Independent academic research with Professor Michael Muthukrishna at the LSE found our outputs come back roughly 10,000× faster than traditional methods, at 95% accuracy. AI is part of what we build, but it isn't the product. The hard work is system design, data, orchestration, and making outputs trustworthy enough that people act on them. Running population-scale simulations is a systems problem as much as a science one — foundation models, behavioural data, evaluation pipelines, and the infrastructure that holds them together, with real engineering problems at every layer.
How the work gets done here isn't handed down — it's worked out by the people closest to it. You'd help shape what gets built or sold and why, decide where the trade-offs sit between speed and depth, and judge when something is ready for customers and when it needs another pass. What the role involves day-to-day, what your first six months look like, and how compensation, equity, growth and flexible working are structured are all set out in detail below — the headline is that early joiners get meaningful equity, a clear path to grow with the company, and the flexibility to work around the rest of your life.
Electric Twin was founded by Dr Ben Warner (former Chief Data Advisor to the UK Prime Minister) and our CEO, Alex Cooper (a former senior military commander and Director of Mass Covid Testing in the pandemic). We're backed by top tier investors including Atomico, LocalGlobe, Mercuri, and angels including Marc Andreessen. We have a high-class team of engineers, AI researchers, behavioural scientists, and operators — careful with the science, careful with the responsibility."
The Role
As an Insights 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 behavioral 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.
What You'll Do
Transform Datasets to Onboard onto our Product: Design synthetic population queries by onboarding custom datasets for customers
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.
Bring the platform to life: Work with the product team to understand the best use cases for customers in order to show them how to best address their pain points and use cases.
Top and Tail Customer Requirements from our platform: From running the data collection and onboarding to build out the desired synthetic audience, to making recommendations and delivering outputs against customer briefs.
Who You Are
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Quantitative degree (mathematics, statistics, economics, physics, computer science, psychology, or related field)
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1-3 years in data analysis, market research, consulting, or customer-facing technical roles
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Excellence at translating complex technical concepts for non-technical executives
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Proven ability to manage sophisticated customer relationships independently
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Thrives in ambiguous, fast-moving startup environments
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UK work authorisation required
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Proficient in Python
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Quick learner who can master new AI/ML platforms and concepts
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Be able to identify root cause of technical issues in data and evaluation pipelines
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Experience with LLMs, AI systems, or enterprise SaaS implementations
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Management consulting background, especially in technology transformation
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Track record presenting to C-suite executives
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Knowledge of behavioral science or consumer insights
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High levels of self-discipline and organisation
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Intellectually curious with exceptional attention to detail
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Builds trust quickly with senior stakeholders
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Comfortable with high-stakes decisions and broad responsibilities
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Strong ownership mentality with composure under pressure
Essential Qualifications
Technical Skills
Desirable Experience
Personal Attributes