Senior Data Analyst

Raft
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst - HOTH, Permanent

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Raft is the intelligent logistics platform that’s rewriting the technology playbook for freight forwarders and customs brokers in the automation era. A dynamic UK-based technology company that’s fundamentally reshaping international logistics, we’re searching for a Data Analyst who is excited by the prospect of working in a rapidly growing scale-up. We have significant runway thanks to funding from leading US investor Bessemer Venture Partners (LinkedIn, Twilio, Shopify), alongside Episode 1 (Zoopla, Betfair, Shazam) and supply chain-focused fund Dynamo Ventures (Sennder, Stord).

We are looking for a data analyst to help us make better business decisions using information from our available data. Your task is to gather and prepare data from multiple sources, run statistical analyses, and communicate your findings in a clear and objective way.

Day to Day you will engage in:

  • Developing data models,pipelines and visual dashboard interfaces to provide insights at scale, solving for both Raft and our customers
  • Conduct deep analysis and provide insights to support the growth and expansion of our business
  • Collaborating with teams across Raft to solve critical business problems in a data driven methodology
  • Ability to define and create metrics for the businesses performance and drive insights for customers at scale 

Requirements

We specifically want someone who is/has:

  • 5+ years of relevant work experience, ideally in a fast-paced tech environment 
  • SQL expert and Python proficiency 
  • Expert in data analysis and communication, conducting exploratory data analysis, and crafting data-driven reports and visualizations
  • Ideally a mathematics, engineering or another highly quantitative degree from a globally recognized university

Apply because you want to...

  • Have the opportunity to work in a global market and compete with best in class companies who are on the front line of Machine Learning and Engineering developments
  • Work in a modern Product-led company where your contributions are valued and have real-world impact
  • Get exposure to working with stakeholders on a global level across different industries
  • Work in a tech, fast-paced and challenging environment that provides opportunities for professional and personal growth
  • Work in a diverse and multicultural environment

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.