Data Scientist

Role overview Use data science to improve customer and business outcomes across product and operations. You’ll work closely with product managers and business leaders, turning questions about credit, fraud, field operations, and promotions into analyses, experiments, and models that teams can act on.

Responsibilities - Explore customer, merchant, and internal data using statistical methods, visualization, and machine learning. - Develop and assess credit-scoring and fraud-detection approaches. - Design and analyze experiments, including tests of targeted promotions. - Optimize field schedules, agent networks, and internal processes to help teams scale and manage costs. - Build practical heuristics and predictive models grounded in user and operational behavior. - Own projects from problem definition through analysis and clear communication of findings.

Requirements - Bachelor’s degree or higher in a quantitative discipline such as statistics, mathematics, economics, computer science, or engineering. - At least five years in data science, machine learning, or technical analytics. - Strong Python, SQL, and data-visualization skills. - Experience in at least one of machine learning, causal inference, statistical modeling, or A/B testing. - Clear written and verbal communication, including presenting actionable findings to technical and business audiences. - Fluent English.

Nice to have - A master’s degree or PhD. - Experience applying analytics to operations with offline components, such as staff incentive design; French language skills.

Benefits and work setup - Fully remote, with candidates based in specified talent hubs or operating markets in Africa; up to three supported in-person gatherings each year. - Salary listed at $130,600–$236,200 USD depending on level and location, plus equity. - Health coverage and retirement contributions vary by country. Other listed benefits include six months of paid parental leave, fertility assistance, flexible vacation, and charitable donation matching.