[{"content":"I am a Data Scientist working in FinCrime ML at Rabobank, with previous experience as a Data \u0026amp; AI Consultant at Microsoft and as a Data Scientist at Philips. My work sits at the intersection of applied machine learning, cloud data platforms, Responsible AI, and business-facing delivery.\nAcross financial services, enterprise consulting, healthcare, CRM analytics, and research, I have worked on turning ambiguous business problems into data and AI solutions that can be designed, implemented, explained, and used in practice.\nMy recent focus includes financial crime machine learning, generative AI, large language models, NLP, Azure-based data and analytics platforms, and model governance. I enjoy working close to both technical teams and stakeholders: translating needs into architecture, building reliable analytical workflows, and keeping ethical, explainable AI practices part of the delivery process.\nI am especially interested in AI systems that are useful beyond a prototype: solutions that improve decisions, reduce operational friction, and create measurable value while remaining understandable and responsible.\n","externalUrl":null,"permalink":"/about/","section":"Ya Ting Hu","summary":"","title":"About","type":"page"},{"content":"","externalUrl":null,"permalink":"/categories/","section":"Categories","summary":"","title":"Categories","type":"categories"},{"content":" KTH Royal Institute of Technology # 2020-2022 · M.Sc. in ICT Innovation (GPA 9/10)\nSelected courses: Data-Intensive Computing, Data Mining, Innovation Study Project.\nEindhoven University of Technology # 2020-2022 · M.Sc. in Computer Science and Engineering (GPA 9/10)\nPublication: Hu, Y. T., Burch, M., \u0026amp; Wetering, H. van de. (2021). Visualizing dynamic data with heat triangles. Journal of Visualization, 1-15.\nSelected courses: Advanced Algorithms, Machine Learning and Engineering, Big Data Management, Foundations of Process Mining, Applied Statistics, Visual Analytics, Foundations of Data Mining, Applications of Data Science for Software Engineering.\nExtracurricular activities: joined Summer School Internet of Things (IoT) Platforms for Industry 4.0 at Technical University of Munich and served as Student Representative for the EIT cohort Eindhoven 2020/21.\nEindhoven University of Technology | Tilburg University # 2017-2020 · B.Sc. Data Science (Cum Laude)\nPublication: Hu, Y.T., Burch, M., \u0026amp; van de Wetering, H. (2020). Visualizing dynamic graphs with heat triangles. Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, 1-8.\nSelected courses: Multivariate Data Analysis, Data Structures, Cognitive Science, Design for Games and Play I, Mathematical Analysis 1 and 2, Process Theory, Business Analytics, Data Science Research Methods, Statistical Computing, Linear Optimization, Linear Algebra, Law and Data Science.\nExtracurricular activities: organised and promoted the Data Science Summit 2019 with 350 visitors to showcase interesting scientific research done in close collaboration with and inspired by the industry at the Eindhoven Artificial Intelligence Systems Institute (EAISI), previously known as Data Science Center Eindhoven (DSCE).\n","externalUrl":null,"permalink":"/education/","section":"Education","summary":"","title":"Education","type":"education"},{"content":" Data Scientist, Rabobank # May 2025 - Present · Utrecht, Netherlands\nWorking in FinCrime ML, applying machine learning to financial crime detection and risk-focused decision support.\nDevelop and improve machine learning solutions for financial crime use cases. Work with data, model, and domain stakeholders to translate risk and compliance needs into practical analytical solutions. Contribute to responsible, explainable, and production-aware model development in a regulated financial services environment. Apply data science methods across model experimentation, validation, monitoring, and stakeholder communication. Data \u0026amp; AI Consultant, Microsoft # Sept 2022 - April 2025 · Schiphol, North Holland, Netherlands\nDelivered Data \u0026amp; AI consulting engagements for enterprise customers, translating business needs into technical solution designs and implementation plans across data platforms, business intelligence, advanced analytics, and AI.\nLed Data \u0026amp; AI solution design across customer engagements, connecting business requirements with scalable technical architectures. Developed high-level and detailed design documentation for statements of work, delivery planning, and stakeholder alignment. Implemented modern data and analytics solutions using Microsoft cloud technologies. Supported projects across data platforms, business intelligence, and advanced analytics with a focus on delivery quality and customer value. Mentored fellow consultants and contributed to continuous improvement across project teams. Data Scientist, Philips # Sept 2021 - Aug 2022 · Eindhoven, North Brabant, Netherlands\nWorked on motion-based delirium detection research, combining signal processing, feature engineering, and machine learning methods in a healthcare innovation context.\nReviewed existing literature on motion-based delirium detection methods. Derived features indicative of delirium using accelerometer and 3D depth camera data. Benchmarked motion feature performance across different input signals. Documented scientific and algorithmic findings for research and development stakeholders. CRM Data Analyst, A.S. Watson # Mar 2021 - Aug 2021 · Vilvoorde, Flanders, Belgium\nSupported data analysts in conducting and presenting analyses to various stakeholders. Conducted introductory sessions on Tableau for new colleagues and departments. Assisted in updating recurring reports and suggested improvements for report automation and process efficiency. Familiarized with Adobe Campaign for customer campaign selections and learned retail research techniques, including A/B testing. Teaching Assistant, Eindhoven University of Technology # Sep 2018 - May 2021 · Eindhoven, North Brabant, Netherlands\nDepartment of Mathematics and Computer Science.\nSupported teaching and assessment for more than 150 students across technical courses including Python programming, data science research methods, logic, and mathematics. Research Assistant, Eindhoven University of Technology # Sep 2019 - Apr 2020 · Eindhoven, North Brabant, Netherlands\nDepartment of the Built Environment.\nConducted econometric research combined with machine learning techniques using Python, R, and Stata, focusing on Real Estate Management and Development. ","externalUrl":null,"permalink":"/experience/","section":"Experience","summary":"","title":"Experience","type":"experience"},{"content":"This section highlights selected research and applied data science work. Earlier technical projects are included selectively where they show relevant depth, publication history, or domain experience.\nFinancial Crime Machine Learning # Data Scientist · May 2025 - Present\nApplying machine learning in a regulated financial services environment to support financial crime detection and risk-focused decision-making.\nTags: professional, financial-crime, machine-learning\nEnterprise Data \u0026amp; AI Consulting # Data \u0026amp; AI Consultant · September 2022 - April 2025\nDesigned and delivered cloud-based data, analytics, and AI solutions for enterprise customers using Microsoft technologies, with work spanning solution design, technical documentation, implementation, and stakeholder alignment.\nTags: professional, azure, data-platforms, analytics\nMotion-Based Delirium Detection # Data Scientist · September 2021 - August 2022\nWorked on healthcare research using accelerometer and 3D depth camera data to derive and benchmark motion features for delirium detection.\nTags: professional, healthcare, machine-learning\nVisualizing Dynamic Graphs with Heat Triangles # Creator · February 2020 - June 2020\nDesigned and implemented an overview-based interactive visualization tool for temporally long dynamic graph sequences, applied to US domestic flight data.\nTags: research, visualization, publication\nData Mining # Contributor · November 2021 - Present\nProjects covering textually similar documents, frequent itemsets and association rules, mining data streams, graph spectra, and k-way graph partitioning using JaBeJa.\nTags: research, data-mining\nBig Data Management # Contributor · April 2021 - July 2021\nIn this project we use the Spark platform for processing massive data and discovering minimal non-trivial functional dependencies and soft functional dependencies.\nTags: applied analytics\nData Intensive Computing # Contributor · August 2021 - October 2021\nTwo labs regarding HDFS, HBase, Hadoop, MapReduce, Spark, Spark SQL, Spark Streaming, Structured Streaming, GraphX and project regarding real-time Bitcoin price predictions with news sentiment analysis.\nTags: data engineering, streaming analytics\nHoodFood by Diverse IT # Contributor · February 2019 - April 2019\nHoodFood, a comparison tool which allows customers to compare prices between groceries easily, started by Diverse IT.\nTags: product analytics\n","externalUrl":null,"permalink":"/projects/","section":"Selected Work","summary":"","title":"Selected Work","type":"projects"},{"content":" Core Strengths # Financial crime machine learning and risk-focused analytics Generative AI, LLMs, prompt engineering, and Responsible AI Machine learning, NLP, computer vision, and statistical modeling Azure data platforms, analytics architecture, and cloud delivery Stakeholder-facing solution design, documentation, and consulting Data Science and AI # Python, SQL, R PyTorch, TensorFlow, Keras, scikit-learn NLP, GenAI, computer vision, feature engineering, model evaluation Responsible AI, explainability, model governance, and production-aware ML Cloud, Data, and Engineering # Microsoft Azure, Azure Machine Learning, Azure Databricks Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Azure DevOps, Git, Docker, Kubernetes Microsoft Purview, data governance, and enterprise data platforms Analytics and Visualization # Power BI, Tableau, reporting automation, and stakeholder dashboards Experimentation, A/B testing, CRM analytics, and decision-support analysis ","externalUrl":null,"permalink":"/skills/","section":"Skills","summary":"","title":"Skills","type":"skills"},{"content":"","externalUrl":null,"permalink":"/tags/","section":"Tags","summary":"","title":"Tags","type":"tags"},{"content":"I design and deliver practical Data \u0026amp; AI solutions across financial crime, enterprise cloud, healthcare, and analytics environments.\nData Scientist in FinCrime ML at Rabobank\nFormer Data \u0026amp; AI Consultant at Microsoft\nFocused on GenAI, Responsible AI, machine learning, and cloud-scale analytics\n","externalUrl":null,"permalink":"/","section":"Ya Ting Hu","summary":"","title":"Ya Ting Hu","type":"page"}]