SRB28 Regulatory Paralegal Content Analyst
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Verified 9 Nov 2026The posting does not contain a country restriction that excludes Pakistan.
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Job description
Overview At the employer Limited (CCL), we are committed to global leadership in providing innovative digital solutions that empower businesses to reach their full potential. As a remote-first company, we believe in empowering our employees to work in a way that best suits their individual needs, fostering a culture of flexibility and trust. Since our founding in 2020, we have successfully delivered high-quality resources to our clients in the FinTech sector across various business areas. Read more on the the employer website. Job Summary : This is a structured entry-level role for a law graduate or newly qualified paralegal who wants to build deep expertise in financial services regulation while working at the frontier of regulatory technology. You'll be onboarded and mentored on the regulatory content — we don't expect you to arrive knowing MiFID II. We do expect you to be rigorous, curious, and committed to getting things exactly right. You'll sit at the point where legal source material meets our data pipeline and machine learning models — reviewing regulatory change, validating how our models classify and structure that content, and making sure what appears in our platform matches the authoritative source line for line. You don't need to be a data scientist, but you'll become the human judgment that keeps the machine honest. Review regulatory change • Monitor and review changes to in-scope regulations and exchange rulebooks (e.g. EU and UK financial services regulation, exchange and CCP rulebooks). • Assess what has changed, when it takes effect, and how material it is, and make sure those changes are captured accurately in the platform. • Maintain a clear, auditable record of your review decisions. Validate the ML topic modelling • Review the output of our machine learning topic models to confirm regulatory content is being classified to the correct topics. • Flag misclassifications and edge cases, and provide structured, labelled feedback that …
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