09/28/2025 updated
BA
100 % available
Senior AI/ML Engineer with expertise in credit risk modeling and healthcare recommendation systems
Tokyo, Japan
Worldwide
A/B TestingArtificial IntelligenceAmazon Web ServicesAmazon Elastic Compute CloudAmazon S3Data AnalysisBusiness IntelligencePartnershipsCloud ComputingContinuous IntegrationData CleansingInformation EngineeringExtract Transform Load (ETL)Data VisualizationDevOps
Machine Learning & AI Development
Development of ML-based credit scoring models, recommendation engines, and NLP systems using Python, TensorFlow, PyTorch, and scikit-learn with demonstrated improvements in prediction accuracy.
Data Engineering & ETL Pipelines
Creation of end-to-end data pipelines integrating OCR document ingestion, data cleaning, and ETL processes that reduced manual data entry by 30% and improved data latency by 40%.
Cloud & DevOps
Implementation of cloud-native architectures using AWS (EC2, S3, Lambda, SageMaker), Docker, Kubernetes, and CI/CD pipelines (Jenkins, GitHub Actions) for efficient model deployment and monitoring.
Natural Language Processing
Application of NLP techniques using spaCy, NLTK, and transformer-based models for sentiment analysis, keyword extraction, and content recommendation systems.
Data Visualization & Business Intelligence
Creation of interactive dashboards using Tableau/Power BI to visualize campaign performance and model monitoring metrics for data-driven decision making.
A/B Testing & Analytics
Establishment of A/B testing frameworks to measure impact of new features and recommendation strategies, leading to significant improvements in user engagement metrics.
Cross-functional Collaboration
Partnership with domain experts, product managers, and business stakeholders to translate requirements into technical solutions and ensure alignment with business goals.
Development of ML-based credit scoring models, recommendation engines, and NLP systems using Python, TensorFlow, PyTorch, and scikit-learn with demonstrated improvements in prediction accuracy.
Data Engineering & ETL Pipelines
Creation of end-to-end data pipelines integrating OCR document ingestion, data cleaning, and ETL processes that reduced manual data entry by 30% and improved data latency by 40%.
Cloud & DevOps
Implementation of cloud-native architectures using AWS (EC2, S3, Lambda, SageMaker), Docker, Kubernetes, and CI/CD pipelines (Jenkins, GitHub Actions) for efficient model deployment and monitoring.
Natural Language Processing
Application of NLP techniques using spaCy, NLTK, and transformer-based models for sentiment analysis, keyword extraction, and content recommendation systems.
Data Visualization & Business Intelligence
Creation of interactive dashboards using Tableau/Power BI to visualize campaign performance and model monitoring metrics for data-driven decision making.
A/B Testing & Analytics
Establishment of A/B testing frameworks to measure impact of new features and recommendation strategies, leading to significant improvements in user engagement metrics.
Cross-functional Collaboration
Partnership with domain experts, product managers, and business stakeholders to translate requirements into technical solutions and ensure alignment with business goals.
Project history
Designed ML-based credit scoring models improving prediction accuracy by 20%. Built end-to-end pipelines integrating OCR for document digitization. Implemented model monitoring and A/B testing frameworks. Enabled 15% increase in loan approval volume without raising default rates, contributing to 20% growth in loan portfolio and $150K annual savings.
Architected cloud-native backend using AWS Lambda, Docker, and Kubernetes for healthcare super app. Developed personalized recommendation engines using TensorFlow and PyTorch, boosting click-through rates by 25%. Implemented HIPAA-compliant data practices and optimized data pipelines, reducing latency by 40%. Contributed to 50% uplift in user engagement metrics.
Designed complete ML pipelines for digital marketing needs, reducing campaign setup time by 40%. Built NLP models for sentiment analysis and keyword extraction, improving conversion rates by 15%. Developed recommendation systems leading to 20% lift in email click-through rates. Automated marketing tasks saving the team 15 hours per week and increasing campaign ROI by 25%.