Tomasz Rey
Total Rewards expert with deep experience in compensation policy, compliance, and data analytics. Combines HR advisory expertise with hands-on Total Rewards practice.
Evaluate every job description. Spot what's missing, complete with AI, publish with confidence.
Transparent grading across six dimensions. Every score broken down, every decision defensible - no black boxes.
Measure how your workforce is built. Grade distribution, pay gap, and outliers - across every family, every level.
Walk into any compensation review and you’ll hear the same question from the board: why is this role graded the way it is? In traditional systems, the honest answer is often uncomfortable - because a consultant said so, or because that’s what the model produced. The reasoning sits inside a proprietary weighting scheme no one outside the vendor has ever seen.
For years, opacity was the industry standard. Compensation teams lived with it because the alternative - building from scratch - wasn’t practical. Under the EU Pay Transparency Directive, that calculus is changing fast.
Axiomera is built on ESCO - the European Commission’s multilingual taxonomy covering over 3,000 occupations and 13,800 skills across 27 EU languages - and O*NET, the U.S. Department of Labor’s occupational database that has classified American roles for more than two decades.
These aren’t proprietary labels or synthetic training data assembled to look convincing. They’re the same reference frameworks Eurostat, national statistical offices, and employment ministries across Europe already use. When Axiomera classifies a role, it’s speaking the language regulators already speak.
Article 4 of Directive 2023/970 is explicit: pay structures must be based on objective, gender-neutral evaluation criteria measuring skills, effort, responsibility, and working conditions. Our four-dimension framework maps directly to those requirements - not as an afterthought, but as the core architecture.
For every role you grade, you see how the total breaks down. What 120 points of responsibility actually represent. Why skills weight 105 in this case and not 80. Which working conditions factored in, and how much they moved the result. No opaque weightings. No hidden features pulled from a model you can’t inspect.
The four required criteria are where most grading stops. But your organisation likely cares about more - a professional certification that matters in finance, a clearance that matters in defence, a language requirement on European roles. Those become custom criteria you add on top, visible in the same audit trail, weighted the way you decide.
A graduate analyst and a Chief Financial Officer sit at opposite ends of almost any pay structure, but the same methodology evaluates both. One audit trail covers entry-level roles, C-suite positions, and everything in between - applied consistently across your entire organisation, not just the roles that happened to be easy to benchmark.
When an employee asks how their role was graded, when a works council requests the methodology behind a pay structure, when a regulator reviews your gender pay gap report - the answer is the same documented file, built the same way, for every role you’ve ever graded.
Total Rewards expert with deep experience in compensation policy, compliance, and data analytics. Combines HR advisory expertise with hands-on Total Rewards practice.
12+ years in People Analytics. Designed the Axiomera methodology and leads the company’s product vision and strategy.
Builds and maintains the server infrastructure, ML inference pipelines, and cloud architecture that powers Axiomera’s real-time job grading engine.
Get in touch to learn how Axiomera can support your pay transparency initiatives.
Get in TouchAI-powered job grading is the process of evaluating and assigning a grade or level to a job role using artificial intelligence - rather than weeks of manual consulting. Axiomera analyses a job description against standardised, gender-neutral criteria (responsibility, knowledge, skills, effort, working conditions) and produces a defensible grade in seconds, including a full breakdown of each dimension.
EU Directive 2023/970 on pay transparency must be transposed into national law by EU member states by 7 June 2026. From that date, organisations with 100 or more employees will be required to report on gender pay gaps and ensure that pay structures are based on objective, gender-neutral job evaluation criteria. Organisations with 250+ employees face earlier and more frequent reporting obligations.
ESCO (European Skills, Competences, Qualifications and Occupations) is the European Commission’s multilingual classification system for occupations and skills. It maps over 3,000 occupations and 13,800 skills in 27 EU languages. Axiomera uses the ESCO taxonomy to classify job descriptions with confidence scores, ensuring consistent, comparable results across your entire organisation.
Job evaluation is the analytical process of assessing a job’s relative worth within an organisation - measuring factors like complexity, accountability, and required knowledge. Job grading is the next step: assigning that evaluated job to a specific grade or band within a pay structure. Axiomera performs both: it evaluates each job dimension individually and then maps the result to a consistent grade scale, giving you a complete, auditable picture.
All employers in EU member states are subject to the Directive, but reporting thresholds are staggered by size. Employers with 250+ employees must report from 2027. Employers with 100–249 employees must report from 2031. Employers with fewer than 100 employees may be required to provide pay information on request. Regardless of size, all employers must use gender-neutral job evaluation criteria - which is where Axiomera helps. Read the full text on EUR-Lex.
Axiomera’s evaluation methodology is built on the criteria defined in Article 4 of Directive 2023/970: skills, effort, responsibility, and working conditions. The grading process is fully documented - every score on every dimension is visible and explainable. There are no black-box outputs. This means your HR team, auditors, or employee representatives can review, challenge, and verify any result at any time.