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- Tasks: Lead the technical strategy and build advanced ML systems in a fast-paced FinTech environment.
- Company: Rapidly scaling Series B FinTech SaaS company with strong VC backing.
- Benefits: Competitive salary, equity options, and a collaborative culture.
- Why this job: Make a real impact on AI innovation in financial services and shape the future.
- Qualifications: Deep expertise in ML, Python skills, and experience in high-growth environments.
- Other info: Mentorship opportunities and a chance to influence key strategic decisions.
The predicted salary is between 78000 - 130000 £ per year.
Location: London Area, United Kingdom (Hybrid)
Salary: Up to £130,000 + Equity
Skills: Machine Learning | AI | Product ML | Deep Learning | Data Platforms
Our client is a rapidly scaling Series B FinTech SaaS business backed by leading VCs. Their platform is used by top financial institutions, digital banks, and emerging fintech innovators to power real-time risk intelligence, automate decisions, and deliver data-driven financial products at scale. As they enter their next growth phase, they are expanding their Data Science function with a Principal Data Scientist who will set the technical direction, drive product-embedded AI, and help shape the future of data intelligence in financial services.
ROLE: Principal Data Scientist
You will be the most senior individual contributor within Data Science — leading technical strategy, architecture, and delivery of advanced ML systems across the platform. You will work closely with Engineering, Product, and GTM teams to build scalable, production-grade AI that directly impacts customers and revenue. This is a hands-on leadership role where you will combine deep technical expertise with product thinking, experimentation, stakeholder influence, and team mentorship.
What You Will Be Responsible For
- Technical Leadership & Strategy
- Define and own the Data Science roadmap across the Series B product suite.
- Architect scalable ML systems and end-to-end pipelines that integrate directly into the core SaaS platform.
- Evaluate emerging models, large language models (LLMs), and deep learning techniques to drive innovation in the FinTech domain.
- Hands-On Modelling & Delivery
- Build, train, validate, and deploy ML solutions across risk modelling, anomaly detection, personalisation, optimisation, and predictive analytics.
- Lead experimentation cycles, champion best practices, and ensure models are production-ready.
- Partner with Machine Learning Engineers to scale models, optimise performance, and improve reliability.
- Cross-Functional Product Impact
- Work with Product to define AI-driven features that enhance customer experience and create commercial value.
- Translate complex modelling outputs into actionable insights for internal and external stakeholders.
- Influence key strategic decisions in a hyper-growth environment.
- Mentorship & Leadership
- Coach and mentor Senior and Mid-Level Data Scientists.
- Advocate for data science best practices across the organisation.
- Represent the team in technical discussions, customer workshops, and industry events.
What You Will Bring
- Deep expertise in ML, statistical modelling, and modern AI techniques (supervised/unsupervised, time-series, Bayesian, deep learning).
- Strong Python engineering skills — NumPy, Pandas, Scikit-Learn, plus PyTorch/TensorFlow.
- Experience building scalable ML systems in production (ML Ops, CI/CD for ML, model optimisation).
- Proven experience in a high-growth environment (startup/scale-up preferred).
- Exceptional communication and stakeholder management skills — able to influence at all levels.
- Strong understanding of financial services, risk, compliance, or decision-science is a bonus.
- Passion for innovation, experimentation, and solving complex problems with data.
Why Join?
- High ownership role at the forefront of a scaling FinTech SaaS product.
- Direct impact on roadmap, technology choices, and the future of AI within the organisation.
- Equity in a fast-growing Series B business with strong backing and market momentum.
- Collaborative, engineering-led culture with room to innovate.
Apply now to become the driving force behind next-generation AI in FinTech.
Principal Data Scientist employer: Loop Recruitment
Contact Detail:
Loop Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist
✨Network Like a Pro
Get out there and connect with people in the FinTech space! Attend meetups, webinars, or industry events. You never know who might be looking for a Principal Data Scientist or who can put in a good word for you.
✨Show Off Your Skills
Create a portfolio showcasing your projects and achievements in machine learning and AI. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can bring to the table!
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice explaining your thought process clearly and confidently. Remember, they want to see how you think, not just the final answer!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It shows you're genuinely interested and helps us keep track of your application. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Principal Data Scientist role. Highlight your expertise in ML, AI, and any relevant projects you've worked on that showcase your ability to drive innovation in a fast-paced environment.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about this role and how you can contribute to our mission. Share specific examples of your past achievements in data science and how they relate to the responsibilities outlined in the job description.
Showcase Your Technical Skills: Don’t shy away from detailing your technical prowess! Mention your experience with Python, ML Ops, and any frameworks like PyTorch or TensorFlow. We want to see how you’ve applied these skills in real-world scenarios, especially in scalable systems.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the quickest way for us to receive your application and start the conversation about how you can help shape the future of data intelligence in financial services.
How to prepare for a job interview at Loop Recruitment
✨Know Your ML Inside Out
Make sure you brush up on your machine learning knowledge, especially around the techniques mentioned in the job description like deep learning and statistical modelling. Be ready to discuss your past projects and how you've applied these concepts in real-world scenarios.
✨Showcase Your Leadership Skills
As a Principal Data Scientist, you'll be expected to lead and mentor others. Prepare examples of how you've influenced teams or driven technical strategy in previous roles. Highlight your experience in cross-functional collaboration, especially with Product and Engineering teams.
✨Prepare for Technical Challenges
Expect to face some technical questions or case studies during the interview. Practice explaining complex ML concepts in simple terms, as you'll need to communicate effectively with stakeholders at all levels. Consider doing mock interviews to get comfortable with this.
✨Understand the FinTech Landscape
Familiarise yourself with the current trends and challenges in the FinTech sector. Be prepared to discuss how your expertise can drive innovation in financial services and how you can contribute to the company's growth. Showing that you understand their market will set you apart.
