HR Data Analyst (SuccessFactors Reporting)

Frazer Jones
London
4 days ago
Create job alert

I am excited to recruit an HR Data Analyst with a focus on SuccessFactors Reporting and Analytics, on behalf of a fantastic business based in the heart of London. SuccessFactors Analytics is an essential requirement for this role. This position plays a crucial role in leveraging people data to inform strategic decisions and improve organizational efficiency. You will be responsible for examining workforce trends, creating insightful reports, and supporting leadership with data-driven recommendations. Your expertise in data analysis will empower HR teams to optimize processes, enhance employee experience, and strengthen overall business performance.


Key Responsibilities


  • Utilise SuccessFactors analytics and reporting, alongside PowerBI and Excel, to manipulate and analyse HR data.
  • Gather, structure, and interpret HR-related data from multiple sources, including HR systems, employee surveys, and workforce evaluations.
  • Keep up with industry benchmarks and HR analytics trends, applying learnings to refine existing models.
  • Participate in HR tech implementations, system upgrades, and automation projects to streamline data workflows.
  • Safeguard sensitive information, ensuring data compliance and adherence to privacy regulations.
  • Assist with regulatory reporting, compliance audits, and workforce analytics requests.
  • Ensure data integrity and consistency, identifying discrepancies and implementing corrective measures.
  • Design custom reports, dashboards, and trend analysis visuals to make complex information more accessible for stakeholders.
  • Detect patterns, correlations, and workforce behaviours that impact recruitment, retention, and performance management.
  • Partner closely with HR and business leaders to translate organisational needs into actionable data insights.
  • Recommend process improvements based on quantitative findings, supporting initiatives that boost efficiency and employee engagement.
  • Monitor data quality, flag inconsistencies, and ensure alignment with best practices for accurate reporting.
  • Provide coaching and training to HR teams on data tools, visualisation techniques, and reporting best practices.
  • Continually assess opportunities for process optimisation, automation, and efficiency improvements.
  • Experience handling HR data analysis, workforce reporting, and trend visualization.
  • Proficiency in data visualization platforms, such as Power BI, Tableau, or advanced Excel functions.
  • Strong understanding of HR metrics, workforce trends, and compliance standards.
  • Proven ability to support system upgrades, process automation, and data migration projects.
  • Adept at working with stakeholders across HR, finance, and operations, ensuring clear communication of data-driven insights.
  • Knowledge of data governance principles and privacy regulations within HR analytics.


The role offers a competitive package of up to £50,000 p.a. on a permanent basis + bonus and benefits. You will benefit from an agile and hybrid working model and be given autonomy. If you’re interested in this role and would like more information, please apply and contact Anton Blades at Frazer Jones via with any questions or to have a confidential discussion about your job search. I am recruiting heavily within the HRIS space, I am super keen to speak with you even if the above role isn’t the perfect match or what you’re looking for. Let’s pick up a conversation.

Related Jobs

View all jobs

Hr Data Analyst

HR Data Analyst (SuccessFactors Reporting)

People data analyst

Employee Benefits Administrator

HR Generalist/Data Analyst 6m FTC

HR Systems and Data Analyst

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.