opengreenhousequmracapital
Data Science Team Lead
Riskified
LocationLisbon
Last observed2026-06-13 05:24:38.234475
Job idqumracapital-riskified:greenhouse:8505605002
About Us Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Acer, Gucci, Lorna Jane, GoPro, and many more . We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day. About the Role The Data Science department plays a pivotal role in our company, generating value to Riskified by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Science Team Leader, you will lead a talented team of data scientists while maintaining hands-on involvement in complex technical projects. You will be responsible for recruiting, mentoring, and developing team members while ensuring the delivery of high-impact machine learning solutions for fraud detection and risk assessment. What You'll Be Doing Technical Leadership Define technical approaches for complex data science projects involving tabular data at scale Lead critical projects and contribute code to production systems Establish and maintain best practices for model development, evaluation, and deployment Conduct code reviews to ensure quality, maintainability, and adherence to standards Guide team members through complex technical challenges Team Leadership & Management Recruit, onboard, mentor, and manage data scientists Foster a collaborative, innovative environment that encourages experimentation and knowledge sharing Work closely with data engineers, ML engineers, fraud domain experts, and product managers Define success metrics and demonstrate business value of data science initiatives Forecast team needs and advocate for necessary tools and infrastructure Qualifications Required M.Sc in Computer Science, Mathematics, Statistics, or a related field 6+ years of proven experience designing and implementing machine learning algorithms with tabular data and successfully deploying them to production 3+ years of experience managing and leading data science teams (minimum 3 direct reports) Demonstrated track record in recruiting, interviewing, and hiring data science talent Strong understanding and practical experience with various machine learning algorithms for structured/tabular data Strong programming skills with high standards for code quality - proficiency in Python with experience writing clean, maintainable, production-grade code Experience with data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform large-scale tabular datasets Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems and translate them into actionable solutions Demonstrated ability to lead cross-functional teams and contribute to a positive work environment Advantages Experience in the fraud domain - Strong advantage Experience with Airflow, CircleCI, PySpark, Docker and K8S Life at Riskified We are a fast-growing and dynamic tech company with 7
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