Jiachong Lai
Performance analytics specialist @ Qventus, Inc
About
Data Engineer with strong experience in large-scale data pipeline design, machine learning implementation, workflow and model optimization. Skilled in working with complex healthcare datasets and applying detailed clinical and business logic to ensure accurate project development. Experienced integrating Generative AI (GenAI) and NLP techniques into production workflows to automate analysis and improve decision-making. Proven success in developing NLP and traditional ML models for complex tasks. Passionate about transforming complex data systems into intelligent, production-ready models that drive analytical and compliance outcomes.
Canada
Toronto
Government Administration
Data Build Tool (DBT), Large Language Models (LLM), Natural Language Processing (NLP), Image Recognition, Artificial Intelligence (AI), Prompt Engineering, Version Control, Git, Oracle SQL Developer, PySpark, Cloudera, Hadoop, impala, win32com, Mathematics, Interpersonal Communication, Model Development, Quantitative Analytics, Optimization, Process Automation
Experience

Analytics Engineer
I specialize in automating workflows, optimizing processes and implementing LLM. My expertise includes: -Designed and implemented an internal Python module using PySpark and impala-shell to automate data extraction, transformation, and cleaning from a Hadoop-based data warehouse. The module supports dynamic customization through Excel-based input, allowing nontechnical users to define project specifications without modifying code. It enables complex operations, such as tracing patient history across multiple medical codes, which would otherwise require developers to manu- ally write complex SQL overlay logic for each use case. The module reduces the development time by 90%. With a single-line execution interface, it is accessible to users with no programming experience. GitLab was used for version control to ensure collaboration and consistent code management. -Performed prompt engineering to train an internal Generative AI (GenAI) model, enabling users to interact with Python modules through natural language commands, eliminating the need for programming expertise. -Automated existing SQL scripts using Python, reducing development time by 80% and saving over 100 hours previously spent manually generating quality control (QC) files.

Data Analyst Intern
• Developed a web-based user interface for automating data gathering and acquisition process by Django Framework, generated valuable business intelligence by increasing 50% efficiency of the data acquisition process. • Conducted cloud-based data acquisition process by creating python automation codes, built-in conversion, and modification of customer data in SQL, and participated development of company-specific documentation during conversion. • Worked closely with IT, Document Control, and purchasing and created last time buy tool/database and automated the last time buy process within Oracle, simplified the operation steps to eliminate trivial steps. • Managed reconciliation adjustments to Oracle database to maintain inventory accuracy on company data dashboard. • Acquired related news and tendering information data on specific keywords, integrated the acquired data via multi resources (Excel, txt., CRM), transformed acquired data by required format onto the database. • Ensured correct adoption of required data standards to guarantee consistency across company relevant news and marketing areas, and provided oversight on external partners performing data management activities on the company’s behalf or executing the data management activities internally.
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