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- Tasks: Lead cutting-edge AI product development and translate research into real-world financial solutions.
- Company: Join a pioneering team at 4-Xtra, focused on innovative AI applications in finance.
- Benefits: Enjoy competitive salary, flexible hours, remote work, and an attractive employment package.
- Other info: Collaborate with industry experts and enjoy excellent career growth opportunities.
- Why this job: Make a significant impact in the financial sector using advanced machine learning techniques.
- Qualifications: MSc or PhD in a quantitative field with strong Python and ML experience required.
The predicted salary is between 70000 - 90000 £ per year.
Senior/Principal Data Scientist (ML Engineer) responsible for advancing 4-Xtra's AI-powered extreme values forecasting and synthetic stress scenario generation platforms. The role combines hands-on machine learning research and engineering with production system ownership, working at the intersection of extreme value theory, synthetic data generation, and modern AI technologies including agentic AI. The successful candidate will continuously translate academic research into production-grade financial risk products. They will be working under the line management of Academic Co-Founders (with a combined 50+ years of experience in research and industrial innovation). Familiarity with financial risk concepts is expected to ensure effective collaboration with Senior Financial Services Advisor and alignment with the company's financial services market focus. Interest and capacity to expand the applications of the 4-Xtra ML predictive tools from FinTech to other verticals and application domains (such as HealthTech and environment) is desirable.
Primary Objectives
- Research-driven product development. Lead advanced modelling and AI product development — statistical models, extreme value theory applications, synthetic data generation (SDG), neural network solutions — from research prototype through production deployment. Proactively identify and implement state-of-the-art ML techniques to maintain 4-Xtra's technological competitiveness.
- Platform and codebase ownership. Own the core Python backend codebase supporting the AWS environment (EC2, S3, Lambda, RDS, Elastic Beanstalk), ensuring reliability, scalability, security, and maintainability. Manage CI/CD pipelines and GitLab administration.
- AI-native development. Leverage agentic AI tools, LLM-assisted coding, and modern AI development workflows across the full development lifecycle — code generation, testing, documentation, and infrastructure automation. Continuously evaluate and integrate emerging AI capabilities to accelerate delivery velocity.
- Cross-functional collaboration. Work closely with Academic Co-founders on mathematical models and implementation, and with Senior Financial Services Advisor on domain requirements. Translate quantitative models into product features aligned with financial industry use cases. Participate in client demonstrations and stakeholder engagements as the technical voice of the product.
Personal Specification
Qualifications & Training:
- Essential - MSc or PhD in Statistics, Machine Learning, Computer Science, Mathematics, Physics, or related quantitative discipline.
- Desirable - PhD with published research in machine learning, extreme value theory, synthetic data, or statistical modelling.
Experience:
- Essential - Strong track record building and owning production ML systems and cloud-hosted platforms. Deep Python backend experience. Proven ability to work across research, engineering, and infrastructure in a lean team. Demonstrated ability to translate academic research into working software.
- Desirable - Experience with financial services data, risk models, or regulatory scenarios. Prior work in a startup or early-stage company. Familiarity with financial risk concepts (stress testing, VaR, scenario analysis) sufficient to collaborate with domain experts.
Qualities & Attitude:
- Essential - Research-hungry and intellectually curious — proactively seeks state-of-the-art techniques. Practical, accountable, and comfortable operating across theory, coding, infrastructure, and delivery. Self-directed with strong judgement.
- Desirable - Comfortable engaging with financial industry stakeholders (CROs, risk managers, regulators). Effective at explaining complex technical concepts to non-technical audiences.
Product Knowledge:
- Essential - Expert knowledge of Python, AWS, Git/GitLab, Linux, CI/CD, SQL, and modern ML/statistical methods. Strong grasp of generative models (diffusion, GANs, VAEs), transformers, and probabilistic modelling. Proficiency with AI-assisted development tools (LLM coding assistants, agentic workflows) across the full stack.
- Desirable - Experience with financial data feeds (Bloomberg, Refinitiv) or risk platforms. Frontend development capability (JavaScript/React). Knowledge of extreme value theory or tail risk modelling.
What we offer
- Location - UK or EU based, remote working possible, with occasional in-person onsite meetings as appropriate at the University of Leeds.
- Hours of work - Full-time, flexible working hours by agreement.
- Salary - Competitive, subject to qualifications, experience and performance.
- Employment Benefits - Attractive package.
Principal Data Scientist/Lead ML Engineer in Bradford employer: 4-Xtra Technologies Ltd
Contact Detail:
4-Xtra Technologies Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist/Lead ML Engineer in Bradford
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and data science. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes the process smoother for everyone involved.
We think you need these skills to ace Principal Data Scientist/Lead ML Engineer in Bradford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the role of Principal Data Scientist/Lead ML Engineer. Highlight your expertise in Python, AWS, and machine learning techniques, as well as any relevant financial services experience.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about advancing AI technologies in financial risk products. Share specific examples of how you've translated academic research into practical applications, and don’t forget to mention your interest in expanding ML tools into other domains!
Showcase Your Projects: If you’ve worked on any projects related to extreme value theory or synthetic data generation, make sure to include them! We love seeing real-world applications of your skills, so don’t hold back on sharing your achievements and contributions.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at 4-Xtra!
How to prepare for a job interview at 4-Xtra Technologies Ltd
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning, extreme value theory, and synthetic data generation. Be ready to discuss how you've applied these concepts in real-world scenarios, especially in financial contexts. This will show that you can translate academic research into practical applications.
✨Showcase Your Technical Skills
Prepare to demonstrate your expertise in Python, AWS, and CI/CD pipelines. You might be asked to solve a coding problem or explain your approach to managing a cloud-hosted platform. Practising coding challenges and reviewing your past projects can help you articulate your experience effectively.
✨Engage with the Team
Since this role involves cross-functional collaboration, be ready to discuss how you've worked with diverse teams in the past. Highlight any experiences where you translated complex technical concepts for non-technical stakeholders, as this will be crucial in your interactions with the Academic Co-founders and financial advisors.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's AI initiatives and their applications in different verticals. This shows your genuine interest in the role and helps you understand how you can contribute to expanding their ML predictive tools beyond FinTech. It’s a great way to demonstrate your research-hungry attitude!