Machine Learning - Credit Optimization Professional - FMCG

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 senior hands-on Machine Learning Engineer /Professional with experience in advanced statistical and mathematical modeling to map the credit optimisation and predictive ability of the FMCG sector.

The role will use customer, transactional, financial and behavioral data to develop predictive and optimization models that improve credit decisions across complex FMCG environments.

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

Prediction → Decision → Optimization

• →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 successful candidate will help move credit decision-making from static rules and historical analysis towards predictive, dynamic and data-driven optimization.

Success will be reflected in measurable improvements in:

• 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

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 optimization techniques is expected.

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

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

• 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.