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.
- Knowledge of Snowflake, dbt, or related cloud data warehousing technologies.
- Background in anomaly detection, rule-based AI, NLP, or data reconciliation.
- 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
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.
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