HR Data Analyst

IMC B.V.
City of London
1 week ago
Create job alert
About the role

In this role, you’ll take the lead on HR analytics across both day-to-day reporting and key project work. You’ll keep our regular HR reports running smoothly, finding opportunities to improve and automate them as we grow. You’ll also play an active part in major HR projects, shaping analytical workstreams and advising on data needs. Working closely with colleagues across HR and Business Planning & Analytics, you’ll help turn data into clear, actionable insights for a range of stakeholders.

Your core responsibilities
  • Deliver, refine and automate HR reports and insights for key annual milestones and decision-making forums.

  • Produce monthly HR reporting, including headcount, attrition and recruitment insights.

  • Support Core HR projects by managing data requests and advising on data requirements.

  • Handle ad hoc analysis and reporting requests from the Core HR team.

  • Partner with Business Planning & Analytics to resolve data-quality issues and improve reporting processes.

  • Collaborate with BPA to ensure dashboards are designed and developed to meet Core HR needs.

  • Support the Month-End Validation process across HR datasets.

Your skills and experience
  • Strong background in HR data analytics with the ability to make recommendations and identify reporting gaps.

  • High proficiency in Excel, including working independently with complex datasets.

  • Ability to translate data into clear insights and data-backed recommendations.

  • Proficient in PowerPoint for presenting findings to different audiences.

  • Experience with Workday and BI tools such as Qlik, Power BI or Tableau.

  • Strong team player able to collaborate effectively with cross-functional partners.

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.


#J-18808-Ljbffr

Related Jobs

View all jobs

HR Data Analyst

HR Data Analyst

HR Data Analyst

HR Data Analyst

HR Data Analyst

HR Data Analyst

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.