Full-Stack Data Scientist/Analyst

Model ML
London
1 day ago
Create job alert

Full Stack Data Scientist/Analyst (London)


Company Overview: 


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.


4. Self-serve data products

  • 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.


5. AI-first development

  • 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.

Related Jobs

View all jobs

Lead Full-stack Data Scientist

Senior Data Scientist - IFRS / Credit Risk Modelling

Data Scientist

Graduate Data Scientist

Data Scientist

Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.