1. Uncover high-value opportunities, build a data-driven personalized CRM strategy, propose innovative solutions and gather cross-departmental consensus to promote implementation;
2. Design, develop and deploy batch/stream processing inference pipelines, supporting the establishment of high-level statistical models, machine learning models, and perfect evaluation frameworks and monitoring systems;
3. Carry out end-to-end data exploration and modeling to solve complex business bottlenecks and optimize platform operation performance;
4. Translate complex technical insights into landable business insights and work with stakeholders to optimize models throughout the product lifecycle;
5. Collaborate with management to propose strategies to fully tap the core competencies in the field of coal stove data science and engineering;
6. Promote the implementation of best practices in data analysis, modeling, code quality management and other fields.
1. Have a doctorate/master's degree in statistics, mathematics, computer science or related metrology;
2. 5 years or more of work experience in using advanced analytical techniques/systems to drive strategic business decisions;
3. Proficient in statistical analysis, machine learning algorithms, A/B testing and causal inference;
4. Collaborate with the market, product, and engineering teams to promote rapid product iteration and implement high-impact business functions;
5. Has excellent verbal and written communication skills and is able to influence management decisions;
6. Proficient in Python and SQL programming languages;
7. Achieve CEFR C1 (proficiency) level in Japanese.
Priority Experience/Skills
1. Have a strongOwnership and business thinking, with the performance of taking full responsibility for business KPIs, can transform data science work into quantifiable sales growth;
2. Have the ability to execute efficiently on the ground, overcome technical obstacles, priority adjustments and other issues in a fast-paced environment, and ensure the quality of the project;
3. Have relevant experience in market science or CRM optimization in the rapidly developing technology industry;
4. Have MLOps capabilities and experience as a machine learning engineer developing and operating production-level inference pipelines (batch + real-time stream processing);
5. Have end-to-end leadership in leading large-scale projects, covering the entire process from initial proposal, resource planning to final delivery and post-maintenance;
6. Achieve CEFR B2 (independent use) level in English.