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

Apply Now

Data Scientist

Tomorro
City of London
6 days ago
Create job alert

The role

You will become part of Tomorro's early team, enabling our customers to achieve their GHG emissions objectives with data-driven insights. You have the skills to gather, transform, and analyse data from a variety of sources and with a variety of structures. You'll be able to apply validation and testing techniques to ensure that analytical results are accurate and trustworthy for decision-makers.

Key responsibilities:

  • Enriching raw data to enable analytical insights internally and for customers
  • Sourcing and evaluating third-party data and analytics and developing integration requirements
  • Performing ad-hoc analysis to address customer needs and inform Tomorro's strategy and priorities
  • Developing, validating, and deploying Machine Learning capabilities, both internal and customer-facing
  • Evaluating methodological documentation for environmental emissions factors to determine if they are suitable for a use case
  • Collaborating on the design of data models, technical architecture, data flows, schemas, and API contracts
  • Developing tools to ensure integrity of internal and customer data in the platform or streamline the customer's data integration experience
  • Tracking your work through the software development lifecycle in JIRA, pushing well-documented pull requests for features, and collaborating through review and comments on fellow developer pull requests

About Tomorro

Our mission is to unlock a new concept of value for companies by monetising their real ESG impact. We believe it all starts with transparency and making the invisible visible through data. The second step is actions, for companies to make informed decisions when taking action to drive real-world impact, including achieving their net-zero targets. The last step is value, achieving a new normal where real-world impact is rewarded or penalised on the capital, commercial, or talent markets.

To do so, our objective is to transform climate, social, and governance programmes for companies, from being a side-lined tick-box exercise into an asset, enabling businesses to use the ownership of their ESG position to win deals, lower their costs of capital, and attract and retain talents.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Optimisation)

Data Scientist - Tax & Legal

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.