Financial Data Analyst

The Curve Group
Reading
5 months ago
Create job alert

The Curve Group – Berkshire, England, United Kingdom (Hybrid)


We’re seeking a Financial Data Analyst with a passion for people analytics and a desire to develop their career within Reward and Benefits. This hybrid role offers the opportunity to shape and deliver an exceptional employee experience through data‑driven insights and robust analytical support.


As part of our clients People team, you’ll use your analytical expertise, Excel mastery, and data accuracy to bring clarity to compensation reviews, benchmarking, and benefits initiatives that strengthen engagement and organisational success.


What You’ll Do

  • Partner with HR and business stakeholders to deliver reward and benefits processes that drive engagement and performance.
  • Support annual salary and bonus review cycles through effective use of HR systems and data models.
  • Conduct market benchmarking, job evaluation, and salary survey analysis to inform pay and benefits strategies.
  • Analyse pay equity and internal alignment to ensure fairness, compliance, and consistency across the organisation.
  • Maintain and interpret benefit and engagement data, contributing to wellbeing and reward initiatives.
  • Collaborate with system specialists to identify and implement process improvements within HRIS platforms (e.g. Workday, Dayforce).

What We’re Looking For

  • Advanced Excel skills with strong attention to detail and accuracy in data handling.
  • Confidence working with large and complex data sets, translating findings into clear and actionable insights.
  • Experience with HRIS systems (such as Workday or Dayforce), and a genuine interest in finding system‑based solutions.
  • Strong organisational skills with the ability to manage deadlines, prioritise tasks, and balance multiple projects.
  • Excellent communication and stakeholder management skills, with a collaborative yet independent approach.

Join us in building reward frameworks that inspire, engage, and make a real difference to our people and culture.


#J-18808-Ljbffr

Related Jobs

View all jobs

Financial Data Analyst

Financial Data Analyst – Power BI & BI Insights

Financial Data Analyst

Data Governance Analyst- Alternative Data and Financial Data

Data Analyst / Stafford

Finance Data Analyst — Digital Transformation (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.

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.