# ML Professional - Retail Banking Lending - Credit Optimization

**Company:** [HumanI](null/companies/nGr332A8HccTyWp7s81jfu.md)
**Location:** Athens, Greece
**Workplace:** hybrid
**Employment type:** Full-time

[Apply for this job](null/view/1a0c8df6-af08-47c7-888b-5ca6cb1e4cdf)

## Description

Our partners are one of the most established and larger Financial Technology Group of Companies of SEE.

They are currently expanding their ML credit portfolio solution services and are looking for an **ML Professional in Credit Optimization.**

We are on the search for an **ML Professional in Credit Optimization,** experienced in the use Machine Learning, Data Science and advanced analytics to improve how the Bank makes **retail lending decisions**.

The role sits at the intersection of **Machine Learning, Credit and Business**, using data and predictive models to optimise the way the Bank assesses customers, manages credit exposure and balances **growth, customer value and risk**.

This is a **hands-on ML / Data Science role applied to Credit** — not a traditional Credit Risk position.

**Key Responsibilities**

-   Develop, apply and continuously improve **ML and predictive models for retail lending and credit decisioning.**
-   Use **customer, behavioral and transactional data** to improve systems modeling in **credit assessment, scoring and lending decisions.**
-   Optimize **credit limits, approval strategies and risk-based decision rules.**
-   Identify **patterns and signals** that can improve the prediction of **default, delinquency and customer behavior.**
-   **Analyze portfolio performance** and **translate model outputs into opportunities for better risk-adjusted lending.**
-   Work closely with **Credit Risk, Data Science, Product and Commercial teams** to turn analytics into practical business decisions.
-   Continuously test, challenge and refine existing credit strategies through **data and experimentation.**

**The Impact**

The role will contribute to:

-   Better and more **predictive credit decisions**
-   Improved balance between **loan growth and credit risk**
-   More effective **credit limits and customer exposure**
-   Earlier **identification of credit deterioration**
-   Improved **portfolio quality and risk-adjusted profitability**
-   A more **data-driven and intelligent retail lending strategy**

## Requirements

**What We Are Looking For**

-   Strong hands-on experience in **Machine Learning, Data Science or Predictive Analytics.**
-   Experience applying **ML to Credit, Lending, Risk, Financial Services or another highly data-driven decision environment.**
-   Strong understanding of **modelling, data interpretation and model performance.**
-   Ability to **connect technical analysis with real business and credit decisions.**
-   Strong **analytical thinking, curiosity and a continuous optimization mindset.**
-   Ability to work effectively with both technical and non-technical stakeholders.

## Benefits

-   €3,500+ gross monthly, for payroll employees depending on candidate experience Bonus scheme
-   Private medical insurance
-   Open to increase the amount even further if we need to work with freelancers via invoicing or on a contract basis