Senior Full-Stack Data Scientist - Growth Algorithms
New
J
JobgetherFashion Technology
Based in the United StatesFull-TimeSenior
Salary$180,000–$205,000 USD
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonMachine LearningData scienceData modelingA/B testingLLM
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.
Responsibilities
- 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.
- 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.
- Own the full lifecycle of data science initiatives, from research and problem definition through deployment, monitoring, and continuous improvement.
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