Full Stack Data Scientist London

ModelML Inc.; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading AI firm in London is seeking a Data Engineer to own the entire data stack. You'll build ETLs, productionise models, and ship insights that drive product and operational decisions. The ideal candidate has 4+ years of full-stack data experience, strong Python skills, and expertise with SQL and dbt. Join a dynamic team and take part in a challenging yet rewarding journey in a fast-growing AI environment.

Benefits

Competitive salary + equity

Performance-based incentives

Innovative work environment

Qualifications

• 4+ years of experience across full-stack data: ETL, modeling, analytics, predictive work.
• Comfortable using AI coding tools daily.
• Ability to handle ambiguity, tight timelines, shifting priorities.

Responsibilities

• Build and maintain Python-based ETLs and API integrations into Redshift.
• Create a clean, scalable semantic layer for LLMs to query reliably.
• Ship lightweight but production-ready models: churn prediction, usage-based forecasting.

Skills

Strong Python

Strong SQL

ETL experience

Predictive analytics

Excellent communication

Education

Strong academic background

Tools

Redshift

GitHub Actions

AWS

dbt

Job description

Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever. The round was backed by FT Partners, Y Combinator, LocalGlobe, QED, 13books, and other top global investors, bringing total funding to $90 million.

Job Description:

This is not a standard BI or analytics role. You will own the entire data stack end-to-end: pipelines, models, analytics, monitoring, predictive insights, and the internal data products that power how the company operates.

You’ll build ETLs, productionise models, develop AI-friendly data structures, and ship insights that help us make product, customer, and operational decisions fast. You’ll work directly with founders, engineering, and GTM teams and be responsible for ensuring our data is accurate, reliable, real-time, and self-servable across the business.

This is a high-ownership, high-velocity role. If you enjoy building things from scratch, moving quickly, and turning messy problems into automated systems, you’ll thrive.

Key Responsibilities

• 1. Own the full data pipeline
  • Build and maintain Python-based ETLs and API integrations into Redshift.
  • Manage orchestration via GitHub Actions (currently no Airflow, no Fivetran).
  • Ensure uptime, correctness, and monitoring across all pipelines.
• 2. Build and maintain the full analytics layer
  • Build dbt models that are well-structured, documented, and agent-friendly.
  • Maintain core business metrics, feature usage metrics, customer health signals, and financial KPIs.
  • Create a clean, scalable semantic layer for LLMs to query reliably.
• 3. Predictive analytics & ML
  • Ship lightweight but production-ready models: churn prediction, usage-based forecasting, anomaly detection, upsell signals, etc.
  • Implement monitoring and automate downstream workflows using model outputs.
  • Build dashboards in Looker that expose the right metrics to every team.
  • Make analytics self-serve so anyone in the company can get answers fast.
  • Set up proactive alerting when something breaks, spikes, drops, or trends.
  • Use AI coding tools daily (Cursor, Codex, Claude Code, Windsurf) to increase velocity.
  • Write clean, structured code that is easy for AI agents to navigate and edit.
  • Contribute to internal tools and data products that power Model ML’s agents.
• 6. Cross-functional leadership
  • Work directly with founders, engineering, product, and GTM.
  • Communicate insights clearly and provide data-led recommendations.
  • Help define the company’s strategy around usage-based pricing, client analytics, product telemetry, and internal operational metrics.

What you can expect:

It won't be easy; in fact, it will be very hard.

BUT, it will be a lot of fun.

You need to be comfortable in being uncomfortable; timelines will change, priorities will most likely shift.

Be prepared to sacrifice your work-life balance in exchange for joining an incredible journey and learning a lot along the way.

Requirements:

• Strong academic background.
• 4+ years experience across full-stack data: ETL, modeling, analytics, predictive work.
• Strong Python (for ETLs + analysis).
• Strong SQL and dbt experience.
• Experience building from scratch at a startup (or a strong desire to).
• Comfortable using AI coding tools daily.
• Ability to handle ambiguity, tight timelines, shifting priorities.
• Excellent communication. You must be able to explain what’s happening in the business clearly and quickly.

Nice to Have

• Experience with Redshift, GitHub Actions, AWS.
• Experience in building anomaly detection or metric monitoring systems.
• Experience working with LLMs or designing data layers for agents.

What We Offer:

• You will be working directly with the founders, who have two successful venture-backed exits under their belt.
• Competitive salary + equity.
• Performance-based incentives.
• Opportunity to be instrumental in our expansion into the APAC market.
• Supportive and innovative work environment.

To conclude, we’re building a team of like-minded, incredibly smart, tenacious individuals with relentless work ethic and focus, all driving towards our very clear revolutionary mission. If you match this description, buy into that mission and you’re at a career stage where you’re ready to make your defining statement to the world, please apply.