ML Engineer

• 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.
• Partial compensation for medical insurance, sports activities, and foreign language.
• Work in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.

Do you have experience in Sourcing?, * 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.

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.