Finance Analyst

CV-Library
City of London, City and County of the City of London
12 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Jackson Hogg Newton Aycliffe, United Kingdom

Data Insight Analyst

Applause IT Recruitment Ltd Birmingham, West Midlands (county), United Kingdom
On-site

HR Data Analyst

Allen Associates Headington, United Kingdom

Senior MI & Data Insights Analyst

Aioi Nissay Dowa Europe Forest Hall, Tyne & Wear, NE12 9EZ, United Kingdom
£45,000 pa On-site

AI Engineer

Tatton Recruitment South Bank, London, SE1 9PZ, United Kingdom

TM1 Developer - Senior Planning Analytics

Manpower Lytham, Lancashire, FY8 5PB, United Kingdom
Posted
9 May 2025 (12 months ago)

Duration - end of year 2025

Hybrid working

The main functions of a financial analyst are to gather and analyze financial information; will typically conduct quantitative analyses of information affecting investment programs of public or private institutions. A typical financial analyst is responsible for analyzing and communicating financial information for clients.

The Daily - Major Activities:

  • Assemble spreadsheets and draw charts and graphs used to illustrate technical reports.

  • Analyze financial information to produce forecast of business, industry and economic conditions for use in making investment decisions.

  • Interpret data affecting investment programs, such as price, yield, stability and future trends in investment risks.

    The Essentials:

  • Verbal and written communication skills, attention to detail, and critical thinking.

  • Basic ability to work independently and manage one's time.

  • Basic ability to analyze business trends and project future revenues and expenses.

  • Basic knowledge of economic and accounting principles, the financial markets, and reporting of financial data.

  • Basic knowledge of federal, state, and company policies, procedures and regulations as related to accounting.

  • Previous experience with computer applications, such as Microsoft Word, Excel and PowerPoint, and any other related financial software

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

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.