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: Intermediate (B1) or higher.
  But the most important skill for this position is a proficiency with COBOL (Common Business-Oriented Language) programming language!

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.