Andrew Hong

The client is a pre-IPO software company that provides investment management cloud-based software for the financial industry. I led the design and development of a client reporting solution, a critical component of the investment management solution.

I worked as a data architect on a project to design and build a new generation of experience ratings using Microsoft Azure, Databricks, Python, and C# (front-end).

I led the design and development of a data model, data pipelines, API (Python), and C# front-end.

Led the data analytics team in designing and building cloud-based data analytics solutions to drive customer value in inventory reduction. Drove data analytics strategy and vision, innovation, data analytics solution design, and SAP/ERP integration. Drove solutions for key customers. Grew the company from seed stage to Series B with ARR over $6,000,000 and achieved product-market fit.

Led the development of the LeanDNA Connect data integration product that is reusable and capable of integrating with common ERP, including SAP and SAP HANA. The toolset used includes Pentaho Data Integration, RDB in AWS Cloud Platform, AWS SageMaker, Python, MySQL, Snowflake, SQLite, and Looker (Embedded Analytics).

Led the product lifecycle, data science, and data analytics in the following areas:

• LeanDNA inventory prediction model using ML and data analytics using AWS services.
• LeanDNA algorithms in optimizing order policy for every part.
• Action-based intelligence.
• Executive dashboard in visualizing the inventory reduction opportunities and actions.
• Demand forecasting model using time series with seasonality.
• Led solution deployment for key customers in pilot programs and drove the business results in inventory reduction.

Led the big data solution architecture design for a media entertainment client to enable customer churn analysis and targeted ads. The solution involves customer data lake, EDW, data marts, data visualization and analysis, and machine learning.

Led the MDM solution architecture design for a pharmaceutical client to enable central master data management and integrate master data across SAP, Salesforce, data warehouse, and other systems. The solution involves MDM, data quality, ETL, and data integration.

Designed and developed supply chain dashboards and integrated them into the LeanDNA supply chain analytics SaaS application.

• Designed the overall cloud solution architecture using Looker as embedded analytics inside LeanDNA cloud-based application.
• Used Looker ML for creating data modeling, views, and Looker ML dashboards.
• Designed and built the data models using Looker ML with the back end of SQL database and Snowflake.
• Designed and built supply chain dashboards using Looker ML dashboard for key supply chain metrics such as supplier on-time delivery and quality, providing capabilities to drill down into lower-level dashboards and detail reports.
• Performed super user training to use Looker for ad-hoc analysis to address business questions.

Acted as a data architect for a re-insurance company, led the design and development, data architecture design, data ingestion, and data pipeline in Azure, Databricks, structured, and unstructured data. Enabled data analysis and data science.

The client is a SaaS software company that provides fleet management software. Led the design and implementation of Looker dashboard implementation and data architecture improvement. The dashboard provides a set of operational KPIs to improve efficiency and lower cost. Led the development of the data model, dashboards, widgets, visualization, and overall data architecture.

Led the data analytics team in designing and developing data analytics/data science projects, including:
• Experience Rating tool for actuaries to evaluate historical losses, premium, development, and insight into insurance premiums.
• Intelligent email form recognition system in gaining the insight from emails and insurance claim forms to understand the policy information, claim type, nature of loss, and other key information.
Architected the solution platform using Microsoft Azure, including REST API, data lake, ELT, and front-end.

I designed and developed the data model, ETL data pipelines, and dashboard using Looker for Client's Fleet Management Software Solution. The solution uses Google GCP Cloud, Looker Dashboard Solution, and RDBMS.