About the Role
Lead the design and implementation of scalable data science solutions, mentor team members, and translate business challenges into analytical frameworks.
Responsibilities
- Develop and deploy machine learning models to support product features
- Collaborate with engineers to integrate data pipelines into production systems
- Define success metrics for experiments and product iterations
- Mentor junior data scientists in best practices and technical execution
- Translate business questions into testable analytical hypotheses
- Ensure model accuracy, scalability, and compliance with data governance
- Lead A/B testing design and statistical analysis for feature rollouts
- Communicate technical findings to non-technical stakeholders
- Optimize data workflows for efficiency and reliability
- Drive data quality initiatives across platforms
- Evaluate new data sources for integration potential
- Maintain documentation for models and analytical processes
- Support product teams with forecasting and trend analysis
- Identify automation opportunities in reporting and modeling tasks
- Stay current with industry advancements in machine learning methods
Nice to Have
- PhD in a relevant technical discipline
- Experience managing data science teams
- Prior work in customer-facing product analytics
- Knowledge of natural language processing techniques
- Familiarity with real-time data processing systems
- Experience with MLOps practices
- Contributions to open-source data projects
- Background in retail or e-commerce analytics
- Published research in data science or related fields
- Experience with large language models
Compensation
Competitive salary and performance-based incentives
Work Arrangement
Hybrid remote with core collaboration hours
Team
Cross-functional team focused on data-driven decision platforms
Technology Stack
- Primary tools include Python, Airflow, BigQuery, and Looker
- Models deployed using Kubernetes and Vertex AI
Growth Opportunities
- Path to senior leadership roles in data science
- Regular internal knowledge-sharing sessions
- Budget for conferences and professional development
Available for qualified candidates
