Data Scientist (Risk Modeller)

Join our team as a Data Scientist (Risk Modeller) and work on Credit Risk models, IFRS9/provisioning models, ESG models, and advanced analytics solutions. Lead specific pieces of the modelling effort and develop and maintain Credit Risk models for internal ratings based approach.

Requirements

• 2+ years of previous experience working in Financial/Credit Risk area in banking, financial institution (FinTech) or in other institution using internal ratings based approach (scoring)
• Knowledge of a variety of modelling techniques such as multivariate regressions and models with categorical response variables
• Excellent analytical (including statistical techniques experience), communication, presentation, organizational and problem-solving skills
• Strong MS Office (Excel, PowerPoint, Word, etc.) as well as strong R/Python coding, and SQL skills

Benefits

• Flexibility (Flexible working hours, Hybrid work, and the possibility to work from anywhere in the EU, Iceland, Switzerland, and the UK)
• International teams
• Culture (dynamic environment that keeps you learning, growing, and never bored)
• More vacation (additional weeks of vacation are available to all employees who have been in the company for 1 year or more)
• Volunteer time off (additional days off for volunteering purposes)
• Paid leave (30 fully paid calendar days for military training every year)
• Health benefits (competitive benefits package in addition to your salary that includes health insurance after the first 3 months pass in all three Baltic states)
• Wellbeing (access to tools and resources that help you feel good and be productive at work and in life)
• Professional growth (internal and external training programs, LinkedIn learning, workshops, conferences, online training, etc)
• Special Offer for Luminor products & services (enjoy special offers & pricing for products and services provided by Luminor)
• Gross salary (3200 – 4800 EUR/month, which is to be determined depending on your level of experience and competencies)