Riskified - Data Scientist Team Lead

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 the business value of data science initiatives
• Forecast team needs and advocate for the necessary tools and infrastructure

Qualifications

• 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

Advantage

• Experience in the fraud domain – strong advantage
• Experience with Airflow, CircleCI, PySpark, Docker and Kubernetes

Perks & benefits

• Hybrid mode of work
• Flexible schedule
• Recharge weekends
• Health and dental benefits
• Fully‑stocked kitchens
• Commuter benefits
• Benefits package per month— customizable (e.g., work‑from‑home equipment, gym membership, wellbeing activities, and more)
• Wellness program
• Celebrations and activities
• Team events
• Happy hours
• Riskified gifts and swags
• Volunteer programs
• Personal development
• Global onboarding
• Role‑based technical skills training
• Full access to Udemy

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