3 часа назад
Senior Data Scientist (Credit)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Scientist (Credit) (Credit Risk and Consumer Lending): Building and deploying credit scoring, affordability, and behavioural models for underwriting, pricing, collections, and retention with an accent on credit risk modelling, experimentation, and real-time decision systems. Focus on optimising approval rates, loss rates, and profitability, translating complex analyses into business recommendations, and ensuring ethical model use across large-scale lending decisions.
Location: Remote, Spain
Company
is an African financial platform providing payments, banking, credit, cross-border, and business management tools to businesses and individuals.
What you will do
- Develop and deploy credit scoring, affordability, and behavioural models for underwriting, pricing, and collections.
- Design experiments to optimise approval rates, loss rates, and profitability.
- Partner with product squads to embed decision logic into real-time systems.
- Ensure data quality, regulatory compliance, and ethical use of models.
- Mentor product squads on experimentation and data-driven decision-making.
- Build models to optimise collections, churn management, and user retention.
Requirements
- Degree or equivalent qualification in Statistics, Mathematics, Engineering, or a related quantitative field.
- 5+ years of experience in data science, decision science, or risk analytics within financial services.
- Working knowledge of credit risk, consumer lending, and regulatory considerations.
- Proficiency in SQL and at least one modelling or programming language, such as Python or R.
- Experience with A/B testing, machine learning, collections modelling, and churn management.
- Ability to translate complex analyses into clear recommendations for business stakeholders and work effectively in cross-functional teams.
Culture & Benefits
- People-first culture focused on well-being, inclusion, mutual respect, and open participation.
- Learning and development environment with knowledge sharing, training, and internal technical talks.
- Salary, pension, health insurance, monthly bonuses, and additional benefits.
Hiring process
- Preliminary phone call with a recruiter.
- HackerRank coding exercise covering data science theory, mathematics, statistics, linear algebra, and Python fundamentals.
- Take-home assignment followed by technical and behavioural interviews.
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