Junior Data Analyst

City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Junior Data Analyst

Junior Data Analyst - Power BI / SQL

Trainee Data Analyst Excel, SQL & Power BI)

Senior Data Analyst - Marketing

Data Analyst Placement Programme

Data Analyst Placement Programme

I'm looking for a hands-on Data Analyst to join a leading banking client on an initial 6‑month contract. Ideal for a recent grad or early‑career analyst with strong technical ability.

Key Skills

Advanced Excel
Advanced SQL
Power BI (DAX, modelling)
Python (bonus)
Automation Anywhere experience is a big plus

Experience

Must have Financial Services experience (banking preferred)
Strong exposure to Data Quality (measurement, reporting, dashboards, analysis)
Able to work across large datasets and pick things up quickly

About You

Technical, analytical, proactive
Fast learner, comfortable with new tools/systems
1-3 years' experience or a grad with strong project work/internships

Please click to find out more about our Key Information Documents. Please note that the documents provided contain generic information. If we are successful in finding you an assignment, you will receive a Key Information Document which will be specific to the vendor set-up you have chosen and your placement.

To find out more about Huxley, please visit

Huxley, a trading division of SThree Partnership LLP is acting as an Employment Business in relation to this vacancy | Registered office | 8 Bishopsgate, London, EC2N 4BQ, United Kingdom | Partnership Number | OC(phone number removed) England and Wales

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.