
Forward Deployed Data Analyst at Electric Twin (London, United Kingdom)
Electric Twin· London, United Kingdom· £50k–£70k·
Role details
Job description
The Role
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.
What You'll Do
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.
Who You Are
Essential Qualifications
- 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.
- UK work authorisation required.
Technical Skills
- 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.
Desirable Experience
- 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.
Personal Attributes
- 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.
What We Offer
We offer a competitive package designed to support you properly, not just on paper. Competitive salary. Meaningful equity in a high-potential seed-stage company. Unlimited leave. Take the time you need. Generous matched pension contributions. Private healthcare. Cycle to work scheme. Direct access to and collaboration with world-class founders. Hybrid working from our London office (4 days in office a week). Flexible working around life commitments. We value outcomes over presenteeism.
Why work at Electric Twin
- Culture: Described as a “sports team, not a family” — high-performance, collaborative, and achievement-oriented. They value ownership (“nothing is someone else’s problem”) and move fast with “just enough structure.”
- Remote/Hybrid Policy: Office-first but flexible — Soho HQ in London, with support for remote stints (must plan ahead).
- Perks:
- Private health insurance (Bupa, with option to add dependents)
- Pension scheme (matched 4-8% contributions)
- EMI share scheme for all full-time staff
- Unlimited time off
- £1,000 annual L&D budget
- Bike-to-work scheme (save up to 40%)
- Team: Small (23 people), with a strong engineering and data science bench. Co-founder Dr. Ben Warner is a former Advisor to the Prime Minister on Digital and Data and helped build Faculty AI.