At a Glance
- Tasks: Lead data quality assurance strategy and oversee governance, risk management, and validation frameworks.
- Company: RegGenome is a pioneering regulatory data technology company transforming how regulations are processed using AI.
- Benefits: Enjoy a flexible remote-working environment, 25 days holiday, share options, and personal development time.
- Why this job: Join a high-impact role in a fast-paced environment, driving automation and continuous improvement in data quality.
- Qualifications: 5+ years in data quality or governance, ideally in AI or financial services, with strong leadership skills.
- Other info: Be part of a growing team backed by £15 million in funding, shaping the future of regulatory data.
The predicted salary is between 54000 - 84000 £ per year.
RegGenome is a regulatory data technology company and a leader in the field of computational regulation, transforming how the world processes and consumes regulatory information. We leverage AI to convert human-readable regulations into machine-readable and machine-consumable data.
As a commercial spin-out of the Regulatory Genome Project (RGP)—a pioneering public-private partnership with the University of Cambridge Judge Business School—our mission is to build universal information structures for regulatory data, creating a regulatory commons.
Our team combines deep expertise in AI-driven data processing, NLP/ML models, and regulatory communities. Backed by £15 million in funding, we have secured strong product-market fit and commercial traction with global regulators and financial institutions. With our Series A funding round nearing completion, we are expanding our team to scale our data quality and assurance capabilities.
This is an exciting time to join us as we leverage AI and automation to build a world-leading regulatory data repository.
What we are looking for:
We are searching for a Head of Data Quality to lead and formalize our data quality assurance strategy. This is a critical leadership role, ensuring that our data is accurate, reliable, traceable, and compliant with industry standards. You will oversee data quality governance, risk management, and validation frameworks, ensuring that our AI-driven regulatory data processes meet the highest standards. You will also work closely with data science, engineering, product, and regulatory teams to align data quality initiatives with business goals. This is a high-impact role for someone who thrives on building scalable quality processes, implementing automation, and driving a culture of continuous improvement.
About you:
- You are an experienced leader in data quality, governance, or assurance, ideally within AI, regulatory, or financial services industries.
- You thrive in a strategic yet hands-on role, balancing high-level quality initiatives with execution and process optimization.
- You are comfortable working in a fast-paced, data-driven environment, implementing automation and monitoring solutions for quality control.
- You are proactive, assertive, and detail-oriented, capable of leading cross-functional collaboration on data quality issues.
- You have strong analytical skills and a structured approach to risk management and data validation.
- You are comfortable working in an agile environment, managing priorities and adjusting strategies as needed.
What you’ll do:
- Develop and implement a company-wide data quality strategy, ensuring all data sources, transformations, and AI-driven decisions are traceable, auditable, and compliant.
- Define and monitor key risk areas for data quality, creating robust risk management protocols.
- Oversee automation in data quality monitoring, working with engineering and data science teams to build scalable validation frameworks.
- Ensure AI models produce accurate, explainable, and reliable outputs, implementing testing and feedback loops.
- Establish and enforce Service Level Agreements (SLAs) for data quality issues, ensuring efficient remediation.
- Manage and coordinate quality assurance efforts across teams, ensuring alignment with business objectives and regulatory requirements.
- Lead the Data Quality team, mentoring analysts and driving operational excellence.
- Stay ahead of industry trends in data governance and AI-driven quality assurance, ensuring our strategies remain best-in-class.
What you’ll need:
- 5+ years of experience in data quality, governance, or quality assurance, ideally in AI, regulatory technology, or financial services.
- Strong understanding of data integrity frameworks, compliance requirements, and risk management best practices.
- Experience implementing automated data quality monitoring tools and dashboards.
- Familiarity with AI/ML quality assurance practices, including model validation and explainability.
- Proven leadership and stakeholder management skills, with the ability to drive cross-functional collaboration.
- Comfortable making data-driven decisions, balancing short-term priorities with long-term strategic objectives.
Nice to have:
- Experience working in a growing start-up or scale-up environment.
- Familiarity with Python, SQL, or data pipeline automation tools.
- Experience with Jira, Notion, or other project management tools.
What we offer:
- Market rate salary
- Ample opportunity to grow with the company as we scale
- 25 days holiday in addition to UK Bank Holidays
- Share options
- A flexible remote-working environment
- Laptop
- 5 days a year of personal development time
Head of Data Quality employer: Berg Search
Contact Detail:
Berg Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Quality
✨Tip Number 1
Familiarise yourself with the latest trends in data quality and governance, especially within AI and regulatory technology. This knowledge will not only help you understand the role better but also demonstrate your commitment to staying ahead in the field.
✨Tip Number 2
Network with professionals in the data quality and regulatory sectors. Engaging with industry experts can provide insights into best practices and may even lead to referrals or recommendations for the position.
✨Tip Number 3
Showcase your leadership skills by discussing past experiences where you successfully implemented data quality initiatives. Be prepared to share specific examples of how you drove cross-functional collaboration and improved processes.
✨Tip Number 4
Prepare to discuss your experience with automation tools and data monitoring solutions. Highlight any relevant projects where you have used these technologies to enhance data quality, as this aligns closely with the responsibilities of the role.
We think you need these skills to ace Head of Data Quality
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data quality, governance, and assurance. Emphasise any leadership roles you've held and specific projects that demonstrate your ability to implement quality processes in AI or regulatory environments.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data quality and how it aligns with RegGenome's mission. Discuss your strategic approach to data governance and provide examples of how you've successfully led teams in similar roles.
Showcase Relevant Skills: Clearly outline your analytical skills and familiarity with data integrity frameworks. Mention any experience with automation tools and your understanding of AI/ML quality assurance practices, as these are crucial for the role.
Highlight Cross-Functional Collaboration: Demonstrate your ability to work across teams by providing examples of past collaborations. Highlight how you’ve driven initiatives that required input from various departments, showcasing your stakeholder management skills.
How to prepare for a job interview at Berg Search
✨Showcase Your Leadership Experience
As a Head of Data Quality, you'll need to demonstrate your leadership skills. Prepare examples of how you've successfully led teams in the past, particularly in data quality or governance roles. Highlight any specific achievements that showcase your ability to drive cross-functional collaboration.
✨Understand Regulatory Standards
Familiarise yourself with the regulatory standards relevant to the role. Be ready to discuss how you would ensure compliance and data integrity within the company's AI-driven processes. This shows that you are proactive and understand the importance of regulatory frameworks.
✨Discuss Automation Strategies
Since the role involves implementing automation in data quality monitoring, be prepared to talk about your experience with automated tools and dashboards. Share specific examples of how you've used technology to enhance data quality processes in previous roles.
✨Demonstrate Analytical Skills
The position requires strong analytical skills for risk management and data validation. Prepare to discuss your structured approach to these areas, including any methodologies or frameworks you've employed to assess and improve data quality in your past work.