Risk Data Scientist | Hybrid
Westside Drive In
United States
2 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
Algorithm Design
Big Data
Software Quality
Data Cleansing
Extract Transform Load (ETL)
Data Mining
Python (Programming Language)
Machine Learning
NumPy
Raw Data
Standard Sql
SciPy
+6 more
Feature Engineering
Model Validation
Pandas
Scikit Learn
Statistics Packages
Xgboost
Job description
- Develop, calibrate and validate statistical and Machine Learning models applied to credit risk, including Credit Scoring, Behavioral Scoring and Rating models;
- Extract, process and analyze large volumes of data to identify risk patterns and support predictive modeling;
- Design and implement scalable, efficient and modular Python code throughout the entire model lifecycle, from data preparation and ETL to production;
- Perform quantitative analysis, assess model performance and ensure the robustness and reliability of predictive models;
- Identify and handle data quality issues, including missing values, outliers and inconsistencies;
- Explore and implement advanced algorithms, libraries and methodologies to improve model accuracy and efficiency;
- Document modeling assumptions, technical decisions and analytical results;
- Ensure high standards of code quality, technical accuracy and model performance.
Requirements
- Minimum of 5 years of professional experience in Data Science, Predictive Modeling or related quantitative fields;
- Proven experience in developing Credit Scoring, Behavioral Scoring, Rating or Credit Risk models;
- Advanced proficiency in Python, including hands-on experience with Pandas, NumPy, Scikit-Learn, SciPy, Statsmodels, XGBoost and/or LightGBM;
- Strong knowledge of SQL for data extraction, manipulation and analysis;
- Solid understanding of statistical modeling, Machine Learning algorithms and predictive analytics;
- Experience working with large datasets, data preprocessing, feature engineering and model validation;
- Bachelorβs or Masterβs degree in Mathematics, Statistics, Data Science, Physics, Engineering or a related quantitative field;
- Strong analytical and problem-solving skills, with attention to detail and technical accuracy;
- Ability to explain complex analytical concepts, modeling assumptions and technical results clearly;
- High level of autonomy, ownership and accountability, with a results-oriented mindset.
Benefits & conditions
- Work regime: Hybrid;
- Comprehensive health insurance;
- Meal allowance card of β¬10.20/day;
- Health and wellness promotion policy through ClubIn;
- Exclusive access to the Inoweiser Nautical Club;
- Participation in the Wine Club and team building activities;
- Protocols and discounts in health, wellness, sports, retail and dining;
- Involvement in social and environmental initiatives.
About the company
| Inoweiser | Tech For a Better Future |
Inoweiser - Tech for a Better Future - is a technology group with over 20 years of experience, focused on empowering our clients to tackle complex challenges through innovative solutions.
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