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

Apply Now

Data Scientist

Multiverse
City of London
1 week ago
Create job alert

Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.


Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.


In June 2022, we announced a $220 million Series D funding round co‑led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post‑money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.


But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.


Join Multiverse and power our mission to equip the workforce to win in the AI era.


As a Senior Data Scientist, you will play a pivotal role in steering our Data Science team towards achieving strategic objectives. Your expertise will guide collaborative efforts in product and backend services alike, whilst collaborating with product experts, engineers and other stakeholders from across the organization.


You’ll leverage your advanced analytical skills and understanding of AI and machine learning to drive impactful insights and foster innovative solutions. This dynamic role demands a balance of creativity and analytical rigor within a fast‑paced environment, ensuring quick learning and iteration based on user feedback.


What you’ll focus on

  • Translate complex stakeholder queries and hypotheses into actionable analyses, experiments and AI/ML model requirements.
  • Develop a comprehensive understanding of our data lineage and sources, addressing and mitigating sampling and analytical biases.
  • Oversee the productionisation of analyses and models, ensuring their seamless operation at scale by adhering to software engineering best practices.
  • Drive targeted exploration of our data landscape, ideating and implementing innovative ways to use data for enhancing user engagement on our products
  • Build out our knowledge graph capability for underpinning AI/ML models and agentic workflows
  • Proactively monitor and refine analyses and models, optimizing effectiveness and efficiency while minimizing biases and operational challenges.
  • Evaluate and validate scalable methodologies for data collection and processing, ensuring robust practices are in place.
  • Communicate actionable insights to stakeholders at all levels, bridging the gap between technical concepts and business objectives.

What we’re looking for
Required

  • 5+ years of data science/machine learning experience, with a proven track record in leading complex data projects.
  • Extensive experience in deploying supervised/unsupervised machine learning algorithms and AI tools into production, delivering scalable and effective solutions.
  • Strong proficiency in Python and key libraries commonly used in machine learning (e.g., NumPy, Pandas, Scikit‑Learn, PyTorch, Langchain).
  • Advanced working knowledge of SQL
  • Experience with GitHub for version control.
  • Demonstrated experience productionising ML models and analytic outputs within cloud environments (e.g., AWS, Azure).
  • Understanding of best practices in data protection and information security.
  • A tenacious, curious, and pragmatic approach to problem solving, focusing on creating usable, scalable outputs.
  • Exceptional attention to detail and a strong analytical mindset.
  • A growth‑oriented attitude and a passion for continuous learning and professional development.
  • A commitment to Multiverse’s mission and values.

Non‑Required (But Desirable)

  • Familiarity with the education/skills sector
  • Understanding of the semantic web, knowledge graphs and/or network analytics
  • Direct experience with CI/CD practices (e.g., GitHub Actions).
  • Knowledge of infrastructure as code tools (e.g., Terraform).
  • An advanced degree in a numerical, engineering or related discipline.

Benefits

  • Time off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company‑wide wellbeing days and 8 bank holidays per year
  • Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Gympass and access to Spill - all in one mental health support
  • Hybrid work offering - and the opportunity to take part in our work‑from‑anywhere scheme
  • Team fun - weekly socials, company wide events and office snacks

Our commitment to Diversity, Equity and Inclusion

We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy here.


Right to Work

Do you have the right to work in the UK? Unfortunately, at this time we cannot offer sponsorship for this role and we cannot consider overseas applications.


Safeguarding

All posts in Multiverse involve some degree of responsibility for safeguarding. Successful applicants are required to complete a Disclosure Form from the Disclosure and Barring Service ("DBS") for the position. Failure to declare any convictions (that are not subject to DBS filtering) may disqualify a candidate for appointment or result in summary dismissal if the discrepancy comes to light subsequently.


Seniority level

Mid‑Senior level


Employment type

Full‑time


Job function

Engineering and Information Technology


Industries

Higher Education



#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.