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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 Preston 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 Preston
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A personal connection can often get you a foot in the door faster than a CV.
✨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! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Principal Data Scientist/Lead ML Engineer in Preston
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python, AWS, and machine learning in your application. We want to see how you've used these skills in real-world projects, especially if you've worked on production ML systems before.
Connect the Dots: When you write about your past experiences, try to connect them to the role at 4-Xtra. If you've worked with financial risk concepts or have experience in FinTech, let us know how that aligns with what we're doing!
Be Research-Driven: Since this role involves translating academic research into practical applications, share any relevant research you've done, especially if it relates to extreme value theory or synthetic data generation. We love a good research story!
Apply Through Our Website: Don't forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
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 prepared to discuss how you've worked with diverse teams in the past. Highlight your ability to communicate complex technical concepts to non-technical stakeholders, as this will be crucial when working with financial services advisors.
✨Stay Curious and Proactive
Demonstrate your passion for research and innovation by discussing recent advancements in AI and machine learning that excite you. Show that you're not just looking to fill a role but are eager to contribute to the company's technological competitiveness and explore new applications beyond FinTech.