Senior Data Science Manager

Requirements

• You have over 5 years of experience in a comparable data science role, with a proven track record of delivering high-impact insights
• You bring at least 2 years of experience specifically managing a team of data scientists within a product-focused environment
• You are skilled at working closely with Product, Engineering, and Design leadership to guide product strategy and drive organizational decision-making
• You have an extensive track record in data-informed decision making, including defining success metrics, conducting observational inference, and leveraging experimentation to inform direction
• You possess a strong technical background in a quantitative field and are fluent in modern languages for statistics or data processing (e.g., Python, R)
• You are comfortable with ambiguity and enjoy the challenge of balancing rigorous statistical practice with the speed of results
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
• Experience with Enterprise SaaS products is a strong plus
• If you're interested in this role and don't meet every listed requirement, we still encourage you to apply

• As a Data Science Manager, you’ll lead a team of data scientists working across several product teams to drive common goals, such as acquiring new customers
• You will partner closely with product, engineering, and design leads to set the strategy and direction for the overall team while mentoring your reports in their technical growth
• Manage and lead a team of data scientists partnering with Asana’s product teams
• Partner closely with Product Management, Design, and Engineering leaders to drive high-level strategy
• Implement team practices that empower cross-functional partners to make data-informed decisions, striking a balance between rigorous quantitative methods and speed
• Guide data scientists in their technical and professional development through active mentorship
• Collaborate with recruiting and other data team managers to help grow and scale the organization
• Make hands-on contributions to the team’s work, including designing experiments, building ML models, and answering key questions with data