ML Engineer

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.

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.

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.

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.

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.

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.

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.

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.