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- Tasks: Lead AI/ML strategy and develop models for financial data automation.
- Company: High-growth, VC-backed SaaS firm transforming regulatory compliance.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Join a cutting-edge team making a real impact in the FinTech space.
- Qualifications: Experience in ML model deployment and strong Python skills required.
- Other info: Collaborative environment with a focus on ethical AI and data integrity.
The predicted salary is between 48000 - 84000 £ per year.
Miryco Consultants are working with a high-growth, VC-backed SaaS firm in the RegTech space that’s transforming regulatory reporting and compliance for the world’s largest financial institutions. Their platform automates the reconciliation, validation, and submission of complex derivative transaction data—powering greater accuracy, efficiency, and transparency across capital markets.
As they scale their data and analytics capabilities, the firm is seeking a forward-thinking, technically strong AI & ML Lead to spearhead machine learning strategy, model development, and intelligent automation initiatives across the platform.
This role is ideal for someone with a strong ML engineering background, excellent stakeholder engagement skills, and deep familiarity with financial services data, regulatory logic, or post-trade workflows.
Key Responsibilities:
- Own and evolve the firm’s AI/ML strategy, aligning use cases with product goals and FS client pain points.
- Lead the development of ML models for classification, anomaly detection, NLP, and predictive analytics using Python, scikit-learn, PyTorch, or similar tools.
- Collaborate with data engineering to build reliable, secure, and scalable data pipelines that support training, inference, and monitoring of ML models.
- Drive the operationalisation of ML workflows using modern MLOps tools and frameworks. Ensure reproducibility, versioning, and monitoring of models in production.
- Design solutions in the context of complex, structured financial data—such as trade reporting, EMIR/CFTC records, and regulatory schemas.
- Work closely with product and FS domain experts to translate ambiguous problems into well-scoped ML initiatives. Partner with engineers to embed models into the platform.
- Stay up to date with industry and academic trends in AI/ML, particularly those applicable to RegTech, financial data analysis, or document intelligence.
- Produce clear documentation and educate internal teams on the design, purpose, and behaviour of ML systems.
About You – Required Skills & Experience:
- Proven experience designing and deploying machine learning models in production environments.
- Strong knowledge of Python and common ML frameworks such as scikit-learn, PyTorch, or TensorFlow.
- Experience with MLOps practices and tools (e.g., MLflow, SageMaker, Vertex AI, DVC).
- Familiarity with financial data models, structured datasets, and data validation.
- Understanding of regulatory reporting, trade lifecycle data, or capital markets workflows.
- Experience with cloud platforms such as AWS, GCP, or Azure and scalable data environments.
- Excellent communication skills and ability to present findings to technical and non-technical stakeholders.
Nice to Have:
- Experience in RegTech, capital markets, or post-trade analytics.
- Experience working in B2B SaaS.
- Knowledge of Snowflake, dbt, or related cloud data warehousing technologies.
- Background in anomaly detection, rule-based AI, NLP, or data reconciliation.
- Familiarity with regulatory regimes such as EMIR, SFTR, MiFID II, or CFTC.
- Hands-on experience with version-controlled notebooks, CI/CD for ML, or containerisation (Docker/Kubernetes)
Core Competencies:
- Strong problem-solver with a data-driven mindset.
- Practical and commercially aware in applying AI/ML to FS use cases.
- Independent thinker who thrives in ambiguity and fast-changing environments.
- Collaborative and supportive team player, eager to share insights.
- Committed to ethical AI, data integrity, and model explainability.
Location: London
Office Working: 4 days per week
Please note, our client is unable to offer sponsorship for this opportunity. Finally, should you not be contacted within five working days of submitting your application, then unfortunately you have not been shortlisted for the opportunity. We will however, be in touch should there be any other opportunities of potential interest that are suiting to your skills.
For similar roles, please reach out to Josh Hatton and Tom Parker, and follow Miryco Consultants – LinkedIn
AI & Machine Learning Lead - FinTech SaaS employer: Miryco Consultants Ltd
Contact Detail:
Miryco Consultants Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI & Machine Learning Lead - FinTech SaaS
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those relevant to FinTech. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and tools mentioned in the job description. Be ready to discuss how you've applied these in real-world scenarios, especially in financial contexts.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace AI & Machine Learning Lead - FinTech SaaS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI & ML Lead role. Highlight your experience with machine learning models, Python, and any relevant financial services knowledge. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and ML in the FinTech space. Share specific examples of your past work that relate to the job description—we love a good story!
Showcase Your Technical Skills: Don’t forget to mention your technical skills clearly. Whether it's MLOps tools or cloud platforms, we want to know what you bring to the table. Be specific about your experience with tools like PyTorch or AWS.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any updates from us. Plus, it’s super easy!
How to prepare for a job interview at Miryco Consultants Ltd
✨Know Your Tech Inside Out
Make sure you’re well-versed in the specific ML frameworks mentioned in the job description, like Python, scikit-learn, and PyTorch. Brush up on your knowledge of MLOps tools too, as they’ll likely ask how you’ve used them in past projects.
✨Understand the Financial Landscape
Since this role is in the FinTech space, it’s crucial to have a solid grasp of financial data models and regulatory reporting. Familiarise yourself with terms like EMIR and CFTC, and be ready to discuss how your experience aligns with these areas.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in ambiguous situations. Think of examples where you’ve successfully translated complex problems into actionable ML initiatives, especially in a fast-paced environment.
✨Showcase Your Communication Skills
You’ll need to present findings to both technical and non-technical stakeholders, so practice explaining your past projects clearly and concisely. Highlight your ability to document and educate others about ML systems, as this will be key in the role.
