Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist

MVF
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Our Team

The Data team is a cross-functional team of experienced and passionate data enthusiasts. We use and own modern data tools (Fivetran, Snowflake, dbt, Looker) and cover a diverse range of data problems and stakeholders.

What we're offering you:

  • Flexible hours and summer hours
  • Competitive holiday benefits (25 days a year paid holiday, plus 8 bank holidays)
  • Work from anywhere for 2 weeks a year
  • Life Assurance to protect your loved ones
  • Benefits allowance for health, dental, and vision coverage
  • Defined Contribution Pension and Salary Sacrifice Scheme
  • Be Well: Our award-winning wellbeing and mental health programme to support all MVFers and their families
  • Family Forward support for our MVF parents and their mini-mes
  • Free breakfast when in the office

The Role

MVF is seeking an exceptionally skilled and driven Data Scientist to deliver upon our plans for growth. This is a hybrid-role across Data Science and ML Engineering: we would like someone with either a background in machine learning engineering, but a desire to learn and grow in creating data science products or vice versa.

You will be pivotal in building our Data Science and Machine Learning capabilities in order to hit our strategic goals. These are the problem spaces in our backlog:

  • Recommendation systems - predicting cross-sell opportunities

  • Imbalanced classification - predicting the value of leads

  • Optimisation (e.g., Linear programming) - optimising which leads / products we sell to which client

  • Forecasting - predicting client demand

  • Experimentation


You will be communicative, commercially-minded, with a strong team-spirit. You will enjoy collaborating with stakeholders, as you will be delivering value across the business, from Paid Marketing to Operations and Sales.

Reporting to the Head of Data, you will collaborate closely with a Senior Data Scientist to deliver upon our roadmap. You will have support from Analytics Engineering teams to build and maintain pipelines and from Software Engineering teams to productionize models. The ideal candidate will relish the opportunity to understand their stakeholders more deeply and define where they think they (and Data Science) can add the most value. With support, they will be excited to build data science models from inception to production.

Responsibilities:

  • Build and manage a Machine Learning Platform by selecting and integrating tools that complement the existing data ecosystem (AWS, Snowflake)

  • Productionise ML models, ensuring that they are running scalably, efficiently and robustly

  • Develop Data Science/Machine Learning products addressing key business needs in accordance with ML best practices

What Success Looks Like:

  • Building effective and efficient Data Science models that deliver measurable business value

  • Ensuring Machine Learning is executed using best-in-class tools, techniques, and approaches within budget and time constraints

  • Ensuring exceptional data integrity and quality across all projects

  • Develop ML monitoring and observability pipeline for deployed models

Our Ideal MVF’er:

  • 3+ years of experience in a dedicated Data Science/Machine Learning role; additional data or commercial experience is a plus

  • Strong understanding of mathematical background, focusing on statistics and linear algebra

  • Highly proficient in Python (Pandas, Scikit-Learn, PyTorch, PySpark) and SQL

  • Experience with Snowflake (function & procedure) and Snowpark is a plus

  • Experience with unit and integration tests

  • Strong understanding of machine learning algorithms and best practices

  • Vision for MLOps best practices, particularly regarding version control, Docker, MLFlow, CI/CD

  • Strong communication skills, with the ability to engage effectively with diverse stakeholders

  • Good commercial understanding; knowledge of marketing operations is a bonus

#J-18808-Ljbffr

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.

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.