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; strong analytical and leadership skills.
- Other info: Be part of a growing team backed by £15 million in funding, with opportunities for career growth.
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
Prepare to discuss specific examples of how you've implemented data quality strategies in previous roles. Highlighting your hands-on experience will showcase your ability to balance strategic initiatives with execution.
✨Tip Number 4
Demonstrate your understanding of automation tools and methodologies relevant to data quality monitoring. Being able to speak about your experience with these technologies will set you apart as a candidate who can drive efficiency in 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. Focus on your leadership roles and any specific achievements in AI or regulatory technology that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data quality and how your background makes you a perfect fit for the role. Mention specific examples of how you've implemented data quality strategies and led teams to success.
Showcase Relevant Skills: Emphasise your analytical skills, experience with automation tools, and familiarity with AI/ML practices. Be sure to mention any experience with Python, SQL, or project management tools like Jira or Notion, as these are beneficial for the role.
Highlight Leadership Experience: Since this is a leadership position, detail your experience in managing teams and driving cross-functional collaboration. Provide examples of how you've mentored others and led initiatives that improved data quality and compliance.
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 data quality initiatives, focusing on your ability to drive cross-functional collaboration and mentor others.
✨Understand Regulatory Standards
Familiarise yourself with the regulatory standards relevant to the role. Be ready to discuss how you have ensured compliance in previous positions and how you would approach building a data quality strategy that meets industry requirements.
✨Highlight Your Technical Skills
Since the role involves working with AI and automation, be prepared to discuss your experience with data integrity frameworks and automated monitoring tools. Mention any familiarity with Python, SQL, or data pipeline automation tools to showcase your technical prowess.
✨Demonstrate Analytical Thinking
The position requires strong analytical skills. Prepare to discuss specific instances where you've used data-driven decision-making to solve complex problems, particularly in risk management and data validation contexts.