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Hi, I’m Hanis, a data-driven engineer currently applying ML and data visualization to real-world problems in hospitality and enterprise software. I enjoy turning messy data into clear, actionable insights and collaborating with cross-functional teams to optimize operations. Outside work, I’m passionate about building scalable data pipelines, exploring new AI tools, and mentoring teammates to make analytics more accessible across the organization.…Hi, I’m Hanis, a data-driven engineer currently applying ML and data visualization to real-world problems in hospitality and enterprise software. I enjoy turning messy data into clear, actionable insights and collaborating with cross-functional teams to optimize operations. Outside work, I’m passionate about building scalable data pipelines, exploring new AI tools, and mentoring teammates to make analytics more accessible across the organization.

Hanis Chua Yong Ting

Data Scientist, AI Engineer, Data Analyst, +5

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Hi, I’m Hanis, a data-driven engineer currently applying ML and data visualization to real-world problems in hospitality and enterprise software. I enjoy turning messy data into clear, actionable insights and collaborating with cross-functional teams to optimize operations. Outside work, I’m passionate about building scalable data pipelines, exploring new AI tools, and mentoring teammates to make analytics more accessible across the organization.…Hi, I’m Hanis, a data-driven engineer currently applying ML and data visualization to real-world problems in hospitality and enterprise software. I enjoy turning messy data into clear, actionable insights and collaborating with cross-functional teams to optimize operations. Outside work, I’m passionate about building scalable data pipelines, exploring new AI tools, and mentoring teammates to make analytics more accessible across the organization.

Available to hire

Hi, I’m Hanis, a data-driven engineer currently applying ML and data visualization to real-world problems in hospitality and enterprise software. I enjoy turning messy data into clear, actionable insights and collaborating with cross-functional teams to optimize operations.

Outside work, I’m passionate about building scalable data pipelines, exploring new AI tools, and mentoring teammates to make analytics more accessible across the organization.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Data Scientist Intern at Starbucks Singapore

July 1, 2024 - Present

Automated large-scale Google Reviews processing using Generative AI (LLM) tools on Google Cloud Vertex AI, delivering sentiment and topic insights via Power BI dashboards and reducing manual review effort for stakeholders by ~60%.

Data Science Intern at Certis Cisco

December 1, 2023 - May 1, 2024

Integrated real-time and historical IoT sensor data from Elastic Search into a centralized analytics pipeline and Tableau dashboards, enabling continuous monitoring of restroom cleanliness metrics and next-hour predictions to optimize cleaning operation schedules.

Software Engineer Intern at Cisco

June 1, 2023 - December 1, 2023

Integrated real-time and historical IoT sensor data from Elasticsearch into a centralized analytics pipeline and Tableau dashboards, enabling continuous monitoring of restroom cleanliness metrics and next-hour predictions to optimize cleaning on operational schedules.

Software Engineer Intern at Certis Cisco

June 1, 2023 - December 1, 2023

Built scalable ETL pipelines to share data across 8+ business teams, enabling trusted analytics and cross-store reporting.

AI Virtual Assistant Development Intern at ST Engineering

May 1, 2022 - July 1, 2022

Automated large-scale Google Reviews processing using Generative AI (LLMs) on GCP Vertex AI, delivering sentiment and topic insights via Power BI dashboards, reducing manual review effort by ~60%. Designed an RFM-based customer segmentation framework and supporting CRM campaigns, driving ~15% monthly reactivation of lapsed members. Implemented a prescriptive ordering framework using historical sales and wastage patterns to identify missed opportunities.