Private AI

Data Scientist

• Lead a high-performing team of Japanese language annotators
• Implement training and quality assurance frameworks for consistent, high-quality data annotation
• Establish best practices for Japanese language data processing and annotation standards
• Help design and implement annotation guidelines for complex NLP tasks including Named Entity Recognition (NER), relation extraction, and coreference resolution
• Identify edge cases and model limitations through systematic testing and analysis
• Collaborate with Machine Learning engineers to optimize model performance for Japanese language processing
• Partner with the Japanese sales team to deliver exceptional customer experiences
• Translate client requirements into actionable technical solutions and product improvements
• Research and propose new features based on Japanese market needs and linguistic insights
• Provide expert consultation on Japanese language privacy considerations
• Source and curate high-quality Japanese language datasets for model training
• Develop strategies for handling Japanese-specific PII patterns and cultural considerations
• Ensure data quality through rigorous validation and testing protocols

Data Manager, Japanese Language

Customer Success Manager

• Build a proactive account management function with clear ownership of post-sale relationships.
• Set expansion quotas alongside retention metrics and develop account planning frameworks focused on growth opportunities.
• Deploy automated health scoring based on usage patterns, feature adoption, support sentiment, and engagement.
• Create intervention playbooks and lead weekly account reviews to catch churn risk early.
• Own the customer journey from signature to first value. Implement readiness assessments, 30/60/90-day success milestones, and celebrate early wins to maintain momentum.
• Design and enforce a seamless handoff process—standardized templates, warm handoff meetings, shared context repositories, and a 30-day overlap period with Sales.
• Transform QBRs from status updates into value-delivery sessions with insights, benchmarks, and actionable recommendations.
• Build differentiated SLAs by customer tier, establish clear escalation paths, and implement tools to increase support capacity.
• Develop the CS team, (Director of CS + Solutions Engineer); Own the CS tech stack and build the playbooks that scale.

Data Manager, Japanese Language

Head of Customer Success – VP Level