Senior Full-Stack Data Scientist - Growth Algorithms

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Full-Stack Data Scientist - Growth Algorithms based in the United States.** This is a senior data science opportunity focused on using machine learning and experimentation to shape personalized customer experiences at scale. You will work at the intersection of advanced analytics, traditional machine learning, and Generative AI to solve complex growth challenges. Your work will directly influence customer acquisition, retention, reactivation, and personalized engagement strategies. You will own projects across the full data science lifecycle, from research and experimentation through production deployment and measurement. Using rich behavioral, product, and transactional datasets, you will develop models and insights that guide high-impact business decisions. You will collaborate closely with Product, Design, Engineering, Marketing, and other cross-functional partners to build new experiences and supporting infrastructure. This role is ideal for an experienced data scientist who combines strong technical skills with curiosity, ownership, and a passion for solving ambiguous problems. ### Accountabilities - Design, develop, deploy, and maintain machine learning models and algorithms that support customer growth, personalization, acquisition, retention, and reactivation. - Work across traditional machine learning and Large Language Model (LLM) technologies to identify and implement innovative solutions to complex business problems. - Design and execute online experiments and A/B tests to evaluate new features, models, and customer experiences. - Analyze experimental results and translate findings into clear recommendations for stakeholders and senior leadership. - Develop and optimize Next Best Action models to improve customer journeys and deliver more relevant experiences. - Apply machine learning and analytical techniques to optimize marketing activities across Customer Relationship Management (CRM) and paid media channels. - Leverage large-scale historical datasets covering customer behavior, merchandise, interactions, and engagement to generate actionable insights and predictive solutions. - Account for potential biases, confounding factors, and hidden variables when analyzing large distributed datasets and interpreting results. - Architect technical solutions of moderate complexity and develop reliable, production-grade applications, primarily using Python. - Partner with Product, Design, and Engineering teams to define technical and product roadmaps for new customer experiences, features, models, and infrastructure. - Apply AI-assisted coding practices and agentic product development approaches to improve productivity and accelerate experimentation. - Own the full lifecycle of data science initiatives, from research and problem definition through deployment, monitoring, and continuous improvement. ### **Requirements** - Bachelor's degree in a quantitative discipline such as Computer Science, Statistics, Physics, Mathematics, or a related field; a Master's degree or PhD is preferred. - 5+ years of experience designing, developing, and deploying machine learning algorithms in production environments. - Experience with personalization-focused applications such as recommendation systems, search, customer targeting, or related machine learning use cases is highly desirable. - Strong ability to architect technical solutions of moderate complexity and build production-grade applications, ideally using Python. - Experience working with large-scale and distributed datasets, with a strong understanding of analytical interpretation, bias, confounding variables, and data quality. - Hands-on experience designing and interpreting online A/B tests, experimentation frameworks, and performance metrics. - Applied knowledge of AI-assisted software development practices and experience exploring or building agentic product solutions. - Strong analytical and problem-solving abilities, with the capacity to turn complex data into practical business recommendations. - Excellent communication skills and the ability to explain technical findings, experiment results, and recommendations to both technical and non-technical stakeholders. - Strong sense of ownership and ability to independently manage projects throughout the data science lifecycle. - Collaborative mindset with the ability to work effectively with Product, Design, Engineering, Marketing, and other cross-functional teams. - Comfortable working in an evolving environment, taking on new challenges, learning from failure, and adapting solutions based on evidence and feedback. - Commitment to teamwork and to supporting the growth and success of peers and cross-functional partners. ### **Benefits** - Competitive annual salary of **$180,000–$205,000 USD**. - Annual bonus eligibility. - New-hire and ongoing restricted stock unit (RSU) grants, subject to employee and company performance. - Comprehensive medical, dental, and vision benefits. - Additional health and wellness benefits designed to support employees' overall well-being. - Inclusive workplace culture that values diverse perspectives, collaboration, integrity, innovation, and trust. - Opportunities to work at the intersection of fashion, technology, machine learning, and Generative AI. - Meaningful ownership over projects with direct impact on customer experiences and business growth. - Opportunities for professional development and continued technical growth. - Collaborative environment with strong partnerships across Product, Design, Engineering, Marketing, and Data Science. - Opportunity to contribute to innovative personalization, experimentation, and customer-growth initiatives at scale.