The Senior ML Engineer will spearhead the end-to-end development, deployment, and
stewardship of machine-learning solutions that power credit-risk, collections-strategy,
conversion-optimisation, and fraud-detection processes in MD Finance. Working hand-
in-hand with Risk, Product, Operational and other teams, the role will translate business
goals into robust models, ensure their ongoing performance, and identify new AI/ML
opportunities that raise the company’s bottom line.
Professional qualifications
- 7+ years’ experience in Machine Learning / Data Science, with 3+ years in credit-
- lending organisations.
- Demonstrated delivery and productionisation of Probability-of-Default (PD)models, credit-limit strategies, fraud-detection, conversion-uplift, and collections-
- optimisation models.
- Advanced Python proficiency and solid grasp of modern ML algorithms, feature
- engineering, and model-evaluation best practices.
- Ability to write, structure, and optimise complex SQL queries.
- Deep understanding of the credit lifecycle, especially online lending workflows.
- Proven skill in sourcing, cleansing, and generating features from data sets.
- Comfortable setting up and maintaining modelling environments (local, cloud, or
- on-prem).
- Detail-oriented, accountable, and committed to both team and individual targets.
- English B1 or higher.
Preferred / bonus qualifications
- Practical experience with LLM solutions:
- Using commercial APIs (e.g., OpenAI, Anthropic, etc.).
- Self-hosting of open-source models
- Fine-tuning of open-source models.
- Building voice chatbots.
- Building RAG chatbots.
- Experience with Computer Vision models for document or image processing.
- Building ML pipelines and deploying models to production.
- Creating executive dashboards and model reports in Power BI.
Main responsibilities
- Design, train, and deploy probability of default models.
- Build credit-limit strategies.
- Discover and scope AI/ML opportunities that boost efficiency and revenue of the company, including collections optimisation, fraud control, conversion lift, etc.
- Analyse data sources and engineer features for modelling.
- Produce and update internal model documentation.
- Implement model monitoring.
- Plan and execute A/B tests.
- Build Computer Vision pipelines to automate lending workflows.
- Develop LLM-based solutions that streamline internal processes or enhance customer experience.
Expected results
- Implemented probability of default models and credit-limit strategies.
- Launched A/B tests for models that potentially can boost the efficiency and/or revenue of the company.
- Thorough, audit-ready documentation for models.
What We Offer
- Join a fast-scaling FinTech company where your decisions shape the business and your contributions truly matter.
- Enjoy 20 paid days off annually, flexible scheduling, and a supportive, people-first culture.
- Learning, sports and medical insurance compensation.
- Work in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.