Senior Risk Data Scientist (Python/SQL/Credit Risk) - Hybrid Porto (Up to 2 days/week office, flexible)
- Salary
- €2K–€2.7K/mo
- Hiring from
- Portugal
- Work type
- Hybrid
- Posted
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ABOUT THE OPPORTUNITY
We are looking for a Senior Risk Data Scientist to join a technology organisation developing solutions for the financial services sector. With at least five years of hands-on experience in Data Science or Predictive Modelling, you will take technical ownership of credit risk models and combine advanced quantitative analysis with reliable, high-quality Python development.
PROJECT & CONTEXT
You will develop, train, calibrate and validate statistical and Machine Learning models for credit risk, including credit scoring for origination, behavioural scoring for portfolio management, and rating models. Your work will include interpreting results, making modelling decisions and ensuring 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, taking responsibility for delivery and technical decisions.
Based in Porto, this role offers a flexible hybrid model with up to two office days per week.
WHAT WE'RE LOOKING FOR (Required)
- 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, with the maturity to work independently. This is a senior opportunity.
- Proven involvement in projects developing credit risk, scoring or rating models.
- Advanced Python programming and strong command of the data and Machine Learning ecosystem. Relevant libraries include 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.
NICE TO HAVE (Preferred)
Ability to combine advanced analytical rigour with structured problem-solving.
Compensation: €2,000 – €2,700/month, depending on experience and seniority level.
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