Machine Learning - Credit Optimization Professional - FMCG

humani; Kentucky; On-site; USD 41,000 - 49,000; Full time

Benefits offered by this job

Bonus

Private medical insurance

Ticket restaurants

Job summary

humani is seeking a hands-on Machine Learning Engineer to map credit optimization and predictive capabilities of ML systems using customer, transactional, financial and behavioural data.

The role will develop predictive and optimization models to improve credit decisions across a large FMCG environment, balancing customer value, exposure and risk, with emphasis on turning insights into practical credit recommendations.

Qualifications

• Hands-on experience in credit analytics and credit optimization.
• Strong practical capability in ML, data science, and statistical modelling.
• Experience with high-volume customer-credit environments such as FMCG/retail/finance.

Responsibilities

• Develop and continuously improve credit scoring, behavioural and predictive models.
• Build models to support credit-limit and exposure optimisation.
• Analyse customer payment behaviour and develop early-warning indicators.
• Apply ML and advanced analytics to collections and recovery optimisation.
• Segment customers according to credit behaviour, risk and value.
• Translate predictive models into practical credit recommendations and rules.
• Monitor, validate and continually improve model performance.
• Collaborate with Credit, Finance, Commercial and Data/Technology teams to embed analytical solutions.
• Identify opportunities where better credit intelligence can support commercial growth while reducing risk.

Skills

Credit Analytics / Credit Optimization

Machine Learning

Data Science

Python

R

SQL

Predictive Modelling

Statistical Modelling

Optimization Techniques

Job description

Our partner is specialized in using credit risk assessments for third parties and is one of the most reputable credit optimization subject mater experts of the SEE.

They have recently taken a mandate to Optimize the credit controlling and analysis for a large international FMCG.

They are particularly interested into finding a hands‑on Machine Learning Engineer /Professional thatcan work with advanced statistical and mathematical modeling to map the credit optimisation and predictive ability of the ML systems.

The role will use customer, transactional, financial and behavioural data to develop predictive and optimisation models that improve credit decisions across a complex FMCG environment.

The focus is not simply on assessing credit risk, but on determining the optimal credit decision — balancing customer value, commercial opportunity, exposure, payment behaviour and risk.

Prediction → Decision → Optimization

Key Responsibilities

• Develop and continuously improve credit scoring, behavioural and predictive models.
• Build models to support credit-limit and exposure optimisation.
• Analyse customer payment behaviour and develop early‑warning indicators.
• Apply Machine Learning and advanced analytics to collections and recovery optimisation.
• Segment customers according to credit behaviour, risk and commercial value.
• Translate predictive models into practical credit recommendations and decision rules.
• Monitor, validate and continuously improve model performance.
• Work closely with Credit, Finance, Commercial and Data/Technology teams to embed analytical solutions into business processes.
• Identify opportunities where better credit intelligence can support commercial growth while protecting cash and reducing risk.

The Impact

The successful candidate will help move credit decision‑making from static rules and historical analysis towards predictive, dynamic and data‑driven optimisation.

• Credit decision quality
• Credit‑limit and exposure efficiency
• Bad debt and overdue exposure
• Collections effectiveness
• DSO and cash conversion
• Risk‑adjusted customer profitability
• Commercial value generated through better credit decisions

What We Are Looking For

A hands‑on specialist with experience in Credit Analytics / Credit Optimization and strong practical capability in Machine Learning and Data Science.

Ideally, the candidate will have experience in FMCG, retail, consumer finance, fintech, trade credit or another high‑volume customer‑credit environment.

We are particularly interested in people who have personally built and validated models, rather than only managed analytical teams.

Strong experience with Python and/or R, SQL, predictive modelling, statistical modelling and optimisation techniques is expected.

Above all, the successful candidate will be able to connect:

Credit Expertise + Data Science + Machine Learning + Commercial Judgement

and turn these into better credit decisions and measurable business value.

Core Competences

• Analytical Thinking – able to break down complex credit and customer data into meaningful insights and decisions.
• Commercial Judgement – understands the balance between credit risk, customer value, sales opportunity and cash.
• Problem Solving – translates business problems into analytical and modelling solutions.
• Stakeholder Influence – able to translate complex analytical findings into clear recommendations for Credit, Finance and Commercial stakeholders.
• Ownership & Accountability – takes responsibility for the quality, accuracy and business impact of analytical outputs.

• Circa €3,500 gross for a full time employee plus Bonus, private medical insurance and ticket restaurants, depending on candidate experiences.
• Freelance or contracted /project job professionals will also be considered and with the possibility to increase the payment