Senior Risk Data Scientist, Python/SQL/Credit Risk

HumanIT Digital Consulting

. Develop, train, calibrate and validate statistical and Machine Learning models for credit risk .

Posted 11/4/2026full-timePorto • PortugalSenior💰 €2,000 - €2,700 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and validating statistical and Machine Learning models for credit risk, with a strong command of Python and relevant libraries. Capable of extracting and analyzing large datasets to inform credit scoring and risk assessment decisions.

Highest-signal resume keywords

Python ProgrammingMachine Learning Model DevelopmentCredit Risk ModellingSQL Data ManipulationAnalytical Thinking

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModellingPredictive ModellingData AnalysisETL ProcessesModel ValidationAlgorithm TestingData CleaningScalable Code DevelopmentHandling OutliersDrawing Conclusions from Data

Soft Skills

Attention to DetailTechnical CommunicationTeam CommitmentFlexibilityResilience

Tools & Technologies

PandasNumPyScikit-learnSciPyStatsmodelsXGBoostLightGBM

Industry Keywords

Credit Scoring ModelsBehavioural ScoringPortfolio ManagementRisk PatternsQuantitative Field

Tech Stack

Tools & technologies

ETLNumpyPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Develop, train, calibrate and validate statistical and Machine Learning models for credit risk
Develop credit scoring models for origination, behavioural scoring models for portfolio management, and rating models
Interpret model results, make modelling decisions and ensure analytical robustness and code quality
Extract, process and analyse large datasets to identify risk patterns and interpret predictive model results in their credit risk context
Write scalable, efficient and modular Python code across the model lifecycle, from data cleaning and ETL through to productionisation
Test and implement libraries and algorithms that improve model accuracy and efficiency
Explain technical assumptions and algorithm behaviour clearly
Take responsibility for delivery and technical decisions

Requirements

What you’ll need

Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Physics, Engineering or a similarly quantitative field
At least 5 years of practical experience in Data Science or Predictive Modelling
Proven involvement in projects developing credit risk, scoring or rating models
Advanced Python programming and strong command of the data and Machine Learning ecosystem
Experience with Pandas, NumPy, Scikit-learn, SciPy, Statsmodels, XGBoost and LightGBM
Solid SQL for extracting and manipulating data in relational databases
Strong analytical and critical thinking, including handling outliers and missing values and drawing practical conclusions from complex data
Rigour and attention to detail in code, technical project autonomy and clear technical communication
Ownership, commitment to team objectives, delivery focus, flexibility and resilience
English: B2 or above