Job VC
Senior ML Engineer (FinTech)
Technologies
Description
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.
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.
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.
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.