Senior Data Scientist

• Develop and maintain quantitative models to drive user growth efficiency, including segmentation, propensity, and recommendation models for key problems such as retention, activation, conversion, and monetization.
• Design and analyze A/B tests, uplift experiments, and causal inference studies to measure the true impact of marketing campaigns or policy changes.
• Build and train uplift and causal ML models to identify customers with the highest probability of positive response.
• Develop reinforcement learning and contextual bandit models for personalization, adaptive offers, and dynamic channel allocation; research and implement models that optimize long-term objectives such as Customer Lifetime Value (CLV).
• Design and operate optimization problems for resource, budget, and exposure allocation under real-world constraints and objectives.
• Apply deep learning (embedding, seq2seq, transformer-based recommenders) to capture multidimensional user behaviors and complex signals such as location, device, and transaction sequences.
• Collaborate closely with Product, Growth, Marketing, CRM, and Data Platform teams to deploy models into production and monitor performance accuracy and drift on a quarterly basis.
• Build guardrail metrics and growth simulation frameworks to forecast the long-term impact of product or policy changes.
• Contribute to the development of experimentation frameworks and uplift platforms with ML engineers to automate analysis and reporting.
• Develop reproducible analysis notebooks and dashboards; conduct insight workshops for non-technical stakeholders.
• Optimize data querying and processing workflows using SQL, NoSQL, and Python.
• Enhance and automate data pipelines and streaming data processes for scalability and reliability.
• Optimizing process of access, security and managing infrastructure.
• Mentor and provide technical guidance to junior Data Specialist.
• Propose product improvement ideas and write research reports.