Senior Data Science Manager

About the Role

The role involves defining how the company measures performance, prioritizes investments, and accelerates value creation across the customer lifecycle. You will partner closely with Product, Engineering, Marketing, Sales, and Finance to ensure that the most important decisions are grounded in trusted data and clear experimentation frameworks.

What You Will Do

• Lead and develop a team of Data Scientists embedded across go-to-market, growth product, monetization, and core product experiences
• Define the measurement and experimentation strategy across the customer lifecycle — from acquisition and activation to monetization, expansion, and retention
• Elevate the craft of experimentation, pricing and monetization analytics, and commercial performance measurement
• Partner closely with Product, Marketing, Sales, and Finance to shape roadmaps, evaluate ROI, and guide revenue forecasting and capital allocation decisions
• Translate complex quantitative signals into clear insights that influence product direction and revenue strategy
• Increase team leverage by building scalable analytics systems and self-serve capabilities that power reliable, AI-enabled insights
• Operate effectively in ambiguity, setting clear priorities that balance user value, growth, and long-term business impact
• Collaborate with cross-functional teams to identify and prioritize business problems
• Develop and maintain a deep understanding of the company's products and services

What We Are Looking For

• 10+ years of experience, with 3+ years leading high-performing data teams
• Deep experience in growth, monetization, and product analytics
• Proven track record of partnering with Product, Marketing, Sales, and Finance to shape roadmaps and drive revenue outcomes
• Strong business judgment, with the ability to balance analytical rigor with decision velocity
• Fluency in experimentation design, attribution, and causal inference
• Experience building scalable analytics frameworks and self-serve capabilities
• Thrive in ambiguity, setting clear priorities that balance user value, growth, and long-term business impact
• Excellent communication and collaboration skills

Nice to Have

• Experience working with cloud-based data platforms
• Knowledge of machine learning algorithms and their applications
• Familiarity with Agile development methodologies
• Certification in data science or a related field

Benefits and Perks

• Competitive salary and equity package
• Comprehensive health insurance
• Generous PTO and holiday policy
• Remote work stipend
• Professional development opportunities
• Access to cutting-edge technologies and tools
• Collaborative and dynamic work environment

• To stand out as a candidate, be prepared to showcase your expertise in growth, monetization, and product analytics, as well as your ability to communicate complex quantitative insights to non-technical stakeholders.
• Make sure your resume and online profiles highlight your experience with data science tools and technologies, such as Python, R, and SQL.
• Practice whiteboarding exercises to demonstrate your problem-solving skills and ability to think critically.
• Be prepared to discuss your experience with experimentation design, attribution, and causal inference, and how you've applied these concepts in previous roles.
• Research the company's products and services, and be prepared to discuss how your skills and experience align with their business goals.
• Consider including examples of your work, such as data visualizations or machine learning models, to demonstrate your skills and expertise.