Data Scientist at Worldcoin

Job Description

Key Responsibilities

• Conduct in-depth statistical analyses (e.g., geospatial modeling, causal inference, and predictive analytics) to evaluate market trends, operational bottlenecks, and customer behavior, providing critical input for strategic decision-making.
• Design and implement data visualization frameworks, including interactive dashboards and charts, to communicate complex findings in an accessible manner for non-technical stakeholders.
• Develop self-service data tools and assets that enable the Market Operations team to independently access, analyze, and interpret data without requiring direct intervention from the data science function.
• Collaborate with product managers to identify data requirements and integrate analytics into operational workflows, ensuring solutions align with business objectives.
• Partner with customer support teams to analyze service metrics and identify opportunities for process improvement, enhancing user satisfaction and operational efficiency.
• Work with finance teams to model cost structures, forecast revenue impacts, and evaluate the economic viability of operational initiatives.
• Continuously refine analytical methodologies to improve accuracy, scalability, and relevance to evolving business needs.

Job Requirements

• Master’s or Ph.D. in Data Science, Statistics, Economics, or a related quantitative field, with a proven track record in delivering impactful analytics solutions.
• 5+ years of experience in data science roles, preferably within SaaS, fintech, or operations-focused environments, with expertise in geospatial data analysis and causal inference techniques.
• Proficiency in Python/R for statistical modeling, data wrangling, and machine learning, along with experience in SQL and data visualization tools like Tableau or Power BI.
• Strong analytical mindset with the ability to translate business problems into data-driven hypotheses, and to communicate findings effectively to both technical and non-technical audiences.
• Excellent collaboration skills to work seamlessly with cross-functional teams, including product, customer support, and finance, to ensure alignment with organizational goals.
• Ability to design and maintain scalable data pipelines, ensuring data quality, integrity, and accessibility for operational teams.
• Experience with cloud platforms (e.g., AWS, GCP) and big data technologies (e.g., Hadoop, Spark) to handle large-scale datasets and deliver real-time insights.
• Strong problem-solving abilities with a focus on operational optimization, including experience with A/B testing, process improvement, and performance benchmarking.
• Excellent written and verbal communication skills to document analytical processes, present findings, and collaborate with stakeholders at all levels.
• Ability to work independently and manage multiple projects simultaneously, while maintaining a high level of attention to detail and accuracy.