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;
  • Bachelor’s or Master’s 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 €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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