Jiaxin Xie

Better Regulation Executive (BRE) is a unit within the UK's Department for Business, Energy, and Industrial Strategy (BEIS), and they lead the regulatory reform agenda across government agencies.

Regulation build-ups and changes have made it difficult for policymakers to understand the regulatory landscape, affecting better regulation design. Therefore, BRE is seeking technological solutions to help analyze the cumulative effect of different regulations on business more efficiently.

The solution enhances regulation metadata through natural language processing (NLP), a data science and AI technique, and its back-end API and database. It contains two main sections:

• The "Analysis" section lets users analyze the existing stock of regulations using search, data filter, and visualization, such as pie charts and stacked bars.
• The "Simulation" section enables users to create a draft regulation and analyze its impact on different businesses, for example, visually through charts and contextually through similar or related regulations detected.

This project has two phases:
• Phase 1: a 3-month feasibility study
• Phase 2: a 12-month prototype development

The international aircraft manufacturer has manufacturing and selling sites worldwide in different cities and countries. To manage the manufacturing, logistics, stocking, and selling more efficiently, they needed to redesign the internally used applications to facilitate resource planning and forecasting management.

I started by analyzing their current workflow and app, interviewing different users and stakeholders, designing the solution improvement direction, and managing the development team, including a data engineer, a full-stack developer, and a data architect.

The nonprofit organization is an agency that needs to help innovators grow by giving them support. It needed to increase its impact without significantly raising its headcount. Therefore, a system was required to help its consultants respond more efficiently to innovators' inquiries.

I started by understanding their current workflow by interviewing different roles in the organization and determining the feasibility of using AI with the data scientist. Then, I designed the solution direction: a web application plus a Chrome Gmail add-on. I worked with the UI/UX designer to design the solution and with the tech team, including the front- and back-end developers, to build the application, conduct internal and user testing, and launch and support.

This SaaS application includes regulatory navigation and a quality management system for medical device and pharmaceutical product manufacturers. The application uses NLP and machine learning to automatically analyze applicable regulations specific to medical device or pharmaceutical product development stages, from R&D to pre-market to post-market surveillance.

The application is powered by state-of-the-art AI that helps users classify medical device classes and find suitable SNOMED/GMDN terminology. The application includes a quality management system that supports companies during the whole lifecycle of product development: market and clinical feasibility, clinical trials/evaluation/investigation, company policy assessment, incident/compliance management and analytics, inspection checklist, supplier and distributor management, etc. The application also incorporated a training management system to make it easy for businesses to ensure all staff members have the proper training and qualification level.

The client is an eCommerce startup for sustainable consumer goods: natural home, personal care products, plastic-free and refill packaging, etc. For their marketing team to increase the conversation rate and run a better-targeted campaign, they needed to have a more in-depth analysis of customer behavior.

I analyzed their business model, target customer bases, and current performance, identifying key data points and metrics to measure and study. I managed the data engineers, who transformed the data from different data sources (i.e., their different channels), and the data scientists, who performed the analysis and produced the insight reports. I helped them identify their loyal, repeat customers and their most common order content to target the most valuable customers better. I also helped them to identify their least valuable customers and the common order categories so that they could save costs on the least valuable customers. I analyzed the one-time buyers' behavior to understand their churn and what might cause the customers to leave the site.

The client is a government agency using legacy corporate systems (HR, finance, and planning) that require replacing modernized systems.

WORK DONE
• Conducted the requirement discovery about replacing their corporate systems, namely the financial management system, HR systems, and project management, including interviews, process flow, and recommendation reports.
• Created the documentation of the current system, user profile, and workflow;
• Managed workshops with different teams (e.g., the finance team, the HR team, and the project team) to understand their specific requirements regarding the system they must use.
• Specified the user stories and specifications for the required replacement system and coordinated the search for and evaluation of suitable replacement systems.

The client is a fashion startup that wants to build a platform to produce on-demand custom-made clothes from different designers for different customers.

I conducted user interviews with the three main types of users to understand their needs.
• Fashion designers who want to list their designs on the platform and use the service to manufacture the clothes and sell them to customers.
• Studios that want to supply and produce clothing for fashion designers according to their patterns and specified materials.
• Consumers who wish to have custom-made clothing from their designers.

I translated the user requirements into technical requirements, specified the first MVP features, and managed the development of the first MVP.

I spearheaded the inception, design, and execution of a groundbreaking AI-powered legal technology platform, transforming the landscape of legal research for lawyers. My leadership was instrumental from the initial conceptualization through to the successful market launch, navigating the project through comprehensive stages of idea generation, in-depth interviews with users and stakeholders, and meticulous product design and development.

I leverage advanced extractive and generative AI technologies to analyze a vast array of regulations and case law. This innovative approach not only enhances the efficiency and effectiveness of legal research but also equips legal professionals with unprecedented insights, facilitating a more informed decision-making process.

My role involved orchestrating the ideation process and conducting rigorous market and user research to validate our solution's feasibility and desirability. I led a dynamic team in the product's design and development, ensuring that every feature resonated with our user's needs and industry standards. Post-launch, I remained deeply engaged with our user base, actively seeking feedback to uncover pain points and identify opportunities for further refinement and enhancement.

The client is a large international reinsurance broker with a business intelligence team to manage the data function. I led the R&D team with senior NLP data scientists to explore the use case of generative AI (e.g., LLM, OpenAI) for businesses (e.g., contract analysis) for different purposes, such as operational efficiency improvement and risk mitigation.

The client is a cloud-based venue search platform. Recognizing the need for a more cohesive approach to data analysis and insight generation, I orchestrated the integration of disparate data sources, including Azure search log, an internal database, and Google Analytics, into a singular, centralized BI database. I led the data engineering team to design and implement a robust, automated data processing pipeline. This pipeline facilitated the periodic extraction of critical data needed to compute key performance indicators (KPIs) while also ensuring the data underwent essential transformations—such as filtering, cleaning, and format standardization—to become analytics-ready.

I ensured that once data was preprocessed and stored in the centralized BI database, it was then accessible for comprehensive exploratory analytics. To make these insights actionable and easily interpretable for stakeholders, I led the development of interactive dashboards and reports using Microsoft Power BI. The Power BI dashboard empowered the client to effortlessly access, view, and export reports for high-level meetings and provided them with the tools to drill down into the data on demand.

• I spearheaded the development of an innovative business intelligence solution for a platform serving musicians and venues. We constructed a comprehensive database with over 500,000 global music venues, sourcing data from public networks like Facebook, Songkick, and Google Places.
• Automated data integration: Implemented an ETL solution to continuously update the database with new venues and events, storing daily information in a PostgreSQL database.
• Predictive analytics for strategic opportunities: Developed sophisticated predictive models to identify new opportunities for artists and venues. This included creating genre profiles for venues and artists and analyzing historical data on sentiment, popularity, attendance, and revenue.
• AI-driven tour planning tool: The culmination of this project was an AI tool that aids artists in planning low-risk, successful tours and empowers venue managers to organize profitable events. This tool relies on data-driven recommendations, significantly optimizing event success rates.

The company specializes in providing software solutions that facilitate collecting and displaying diverse user-generated content (UGC) on eCommerce websites. The services encompass product ratings and reviews, Q&A sections, product sampling, visual and social content integration, consumer insights, social commerce, and social publishing.

As a product manager, I spearheaded the development and management of a robust software platform that:

• Enabled retailers to create and manage targeted campaigns, including audience segmentation and performance monitoring.
• Provided logistics and delivery solutions to ensure efficient product distribution.
• Facilitated seamless communication between retailers and consumers.
• Included tools to assess the quality of reviews and gather post-survey insights.
• This comprehensive platform empowered brands to enhance consumer engagement, improve product visibility, and drive sales through authentic user-generated content.