Lead Data Scientist

Accountabilities: Partner with Marketing, Sales, and Customer Experience leaders to identify business challenges, establish analytical priorities, and define data-driven growth strategies. Develop advanced analyses, predictive models, and analytical frameworks to optimize customer acquisition, lifecycle engagement, and retention. Build scalable machine learning solutions, including customer targeting, segmentation, uplift modeling, and lifetime value prediction, to improve growth efficiency and return on investment. Drive acquisition, retention, and monetization initiatives through data-driven experimentation, modeling, and performance measurement. Translate complex analytical findings into clear, actionable recommendations that influence decisions across technical and business teams. Collaborate with engineering teams to deploy machine learning models and analytics pipelines into production, ensuring reliability, scalability, and performance. Stay current with state-of-the-art AI and data science solutions and identify opportunities to apply them to business challenges. Establish best practices for experimentation, measurement, and growth analytics across the organization. Mentor junior data scientists, providing technical guidance and supporting their professional development. Requirements: Bachelor's degree in a STEM discipline required; a master's degree or Ph.D. is preferred. At least 7 years of professional experience in data science, machine learning, or growth analytics, with a demonstrated record of delivering measurable business impact. Expert-level proficiency in SQL and Python, with experience using modern data science and machine learning ecosystems. Strong background in growth-focused data science, including paid marketing optimization, attribution, funnel analysis, experimentation, and customer segmentation. Experience designing and leading complex A/B/n testing frameworks, including multi-armed bandit approaches and causal inference models. Hands-on experience developing, deploying, and maintaining production machine learning models. Familiarity with fine-tuning Generative AI models and large language models (LLMs) for domain-specific applications is an advantage. Excellent communication and storytelling skills, with the ability to explain complex technical concepts to non-technical stakeholders. Ability to navigate ambiguous, zero-to-one problem spaces where established benchmarks or clear ground truths may not exist. Strong product and business intuition, with confidence partnering with senior-level stakeholders and influencing strategic decisions. Experience in consumer-focused businesses, fintech, SaaS, or marketplace environments is preferred. Benefits: Annual salary range of $118,664–$230,619, depending on experience, skills, and location. Location-based compensation ranges, with a stated typical hiring range in California of $139,713–$218,302. Other state-specific ranges are subject to the applicable pay structure. Flexibility to work remotely from anywhere in the United States for most positions. Paid time off, including vacation, sick leave, nine paid company holidays, and volunteer hours. Incentive bonus programs, potentially including holiday, referral, and performance-based bonuses. Medical, dental, vision, life, and pet insurance. 401(k) retirement savings plan with company matching. Education assistance and professional and personal development opportunities. Promotional and career advancement opportunities. Employee recognition program. Health and wellbeing resources, including complimentary mental wellbeing therapy and coaching sessions, as well as childcare and eldercare resources. Engaging and collaborative work environment.