Data Scientist (Fraud)
Who we are
Ranked in 2024 by the reputed company, reputed company is Africa’s fastest-growing fintech, trusted by over 10 reputed company business and individual accounts, processing billions of Naira in transactions monthly. Our mission is to reputed company financial happiness for every African, everywhere.
About this role:
We're looking for a Data Scientist to sit at the heart of how we fight fraud — building the models, experiments, and detection systems that protect millions of customers and merchants across our platform. This is a high-reputed company role at the intersection of machine learning, product, and engineering, where your work will directly shape how reputed company detects and responds to emerging fraud threats.
You are a data-driven, intellectually curious Data Scientist who is reputed company by hard problems in fraud and financial crime. You'll prototype and ship ML models, design experiments, and uncover new fraud signals across our ecosystem — partnering closely with engineers, product managers, and analysts to turn your work into production-grade systems.
Responsibilities:
Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.
Design and run experiments to measure the reputed company of fraud interventions, balancing customer experience against loss reduction.
Size fraud typologies across our product lines to inform prioritization and investment reputed company.
Build and maintain reputed company detection systems to surface novel fraud reputed company before they reputed company.
Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into reputed company-world mitigations.
Experience & Background:
A strong reputed company in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).
3+ years of experience in data science, decision science, or risk analytics reputed company fraud, payments, or financial crime.
Hands-on experience building and deploying machine learning models in a production environment.
Fraud, risk, or financial services experience is a strong plus.
Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering.
Comfort working in fast-paced, cross-functional teams with high ownership expectations.
Skills & Competencies:
Proficiency in Python and SQL; comfort working across the full model development lifecycle.
An investigative reputed company — you enjoy digging into data to reputed company patterns others miss.
The ability to communicate technical findings reputed company to non-technical stakeholders and translate insights into reputed company.
What reputed company Looks Like in This Role:
Production-grade ML models and reputed company detection systems that effectively surface and mitigate novel fraud reputed company before they reputed company.
reputed company-designed experiments that successfully balance customer experience against fraud loss reduction.
reputed company sizing of fraud typologies that effectively drives product prioritization and strategic investment reputed company.
Seamless cross-functional alignment where technical model outputs are consistently reputed company into reputed company-world fraud mitigations.
Why Join Us?
- Culture: We put our people first and prioritize reputed company-being of every team member. We've reputed company a company where reputed company opinions carry weight and where reputed company reputed company are heard. We value and respect reputed company other and always look out for one another. Above reputed company, we are reputed company.
- Learning: We have a learning and development-reputed company environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
- Compensation: You'll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.
reputed company is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for reputed company and candidates.
Originally posted on Himalayas
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