Kreditz is transforming how businesses assess credit and risk using real-time data and NextGen Credit Scoring solutions.
As one of Europe’s fastest-growing FinTech scaleups - we’ve earned a place on the Sifted 100: Nordics & Benelux list in both 2024 and 2025 and most recently, we were proud to receive a double win at the Credit Management & Compliance Awards 2025, being named both "Fintech Rocket of the Year" and "Breakthrough of the Year".
With strong growth across the Nordics and Europe, our clients range from leading banks and iGaming giants to fast-moving digital innovators.
Now, we’re looking for a Junior Data Scientist who can help transform a high-performing fintech into a billion-dollar business.
ABOUT THE POSITION
Kreditz AI/Product team is looking for a Junior Data Scientist to help turn Open Banking transaction data into high-precision credit risk, affordability, and fraud insights. As a regulated AISP and licensed credit reference provider across European markets, Kreditz builds the scoring models, income verifications, and risk detection rules that power modern automated lending. You will work directly on the data analysis, feature engineering, and predictive models behind our core products, alongside our ML Engineers and Senior Data Scientists.
WHAT CAN KREDITZ OFFER
A once-in-a-lifetime growth journey, from startup to Global scaleup
- A journey where everyone in the team plays a crucial role for our company’s success
Fun-loving, driven, and passionate colleagues who support each other’s success
A culture that celebrates progress, humility, and teamwork
24/7 access to gym, sauna and sports facilities at our office, plus additional wellness allowance
Competitive base salary
RESPONSIBILITES
Some of the main responsibilities you will cover:
Perform exploratory and granular data analysis on large-scale Open Banking (PSD2) transaction datasets, uncovering trends in income stability, recurring obligations, discretionary spending, and default behavior across European markets.
Design, test, and document domain-specific features for our transaction categorization engine, credit risk scoring models (e.g., Kreditz Score), and real-time fraud detection systems.
Support model lifecycle and validation: train, validate, and benchmark supervised learning models (logistic regression, XGBoost/LightGBM, decision trees) using cross-validation, hyperparameter tuning, and standard evaluation metrics (AUC-ROC, Gini, KS-statistic, F1-score).
Investigate model behavior and anomalies through root-cause analysis on edge cases, data drift, and performance discrepancies across banking connections, transaction taxonomies, and cross-border implementations.
Collaborate with Machine Learning Engineers to ensure seamless handoff of verified modeling pipelines and features into production.
Translate technical findings into actionable dashboards, model documentation, and clear presentations for product managers, internal risk committees, and external client stakeholders.
WE ARE LOOKING FOR
Bachelor's or Master's degree in Statistics, Data Science, Mathematics, Computer Science, Engineering, Quantitative Economics, or a related quantitative field.
0-2 years of experience with strong proficiency in Python (pandas, NumPy, scikit-learn, SciPy) and advanced SQL for querying large relational and semi-structured datasets.
Solid grounding in statistical inference, probability distributions, hypothesis testing, and supervised learning algorithms, with a strong desire to understand why a model behaves as it does.
Experience using visualization libraries (matplotlib, seaborn, Plotly) or BI platforms to communicate findings to both technical and non-technical audiences.
Proven ability to break down ambiguous, open-ended business questions into structured, hypothesis-driven analyses.
Rigorous approach to data sanity checks, unit testing your analysis, and validating your own results before sharing outputs.
WHY JOIN NOW?
Kreditz is scaling from startup to global fintech leader, and this role sits at the center of that growth: the models you help build directly power automated lending decisions across European markets. You'll join at a stage where your work has outsized visibility and impact, working alongside experienced ML Engineers and Senior Data Scientists while helping shape how the team builds and validates models going forward.
APPOINTMENT OF ROLE
Q3/Q4 2026
SCOPE
Full-time, permanent employment (tillsvidareanställning)
SALARY
Competitive salary
REPORTING
You will be reporting to the company’s CPO
WORKPLACE
Danderyd, Stockholm
RECRUITMENT PROCESS
Ongoing selection, we review candidates continuously.
Last day for applications 2nd October 2026
CRIMINAL RECORDS EXTRACT
As part of our recruitment process we will ask you to present a clean criminal records extract
CONTACT
Lorenzo Puccio, VP Strategic Operations, [email protected]
For more information about the role feel free to reach out to our CPO Spilios Tzouras, [email protected]
