Financial Data Analyst

The Curve Group
Reading
1 week ago
Applications closed

Related Jobs

View all jobs

Senior Reconciliation & Financial Data Analyst

Finance Data Analyst — Digital Transformation (Legal)

Finance Data Analyst — Digital Transformation (Legal)

Data Analyst – Invoicing & Revenue

Data Analyst - Equities (Fundamental & Quantamental) | London

Data Analyst at jobr.pro

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

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.