David Wu found his passion in data and pursued a data science career after witnessing the impact of it on day-to-day business operations.

Can you share the most interesting part of your career journey as an AI expert?

My academic background is in business and accounting. I first started my career in Deloitte’s Audit practice and earned my Certified Public Accountant license. I learned a lot about financial reporting, business operations, and compliance requirements. We adopted a technology-first mindset and analyzed large quantities of financial data to uncover actionable insights. I have witnessed firsthand the evolution of technology and its positive impact on day-to-day business operations. From this experience, I found my passion in data, and I pursued a data science career.

I have witnessed firsthand the evolution of technology and its positive impact on day-to-day business operations. From this experience, I found my passion in data, and I pursued a data science career.

I held many roles at Deloitte and found my passion in technical data analytic and AI assignments. I spent five years managing our retail and consumer product analytic solutions, which focused on business intelligence and process automation. I’m currently aligned to our Audit Innovation initiative, and I get to apply my business background to solve problems using data science and AI.

What excites you most about working with data and AI?

The most exciting aspects about working with data are the business impact and AI use cases. Companies are generating large volumes of complex data points, and finding creative applications using this information is exciting. When executing a project, we spend a lot of time thinking through the business problem, value proposition, and the end-user experience.

The most exciting aspects about working with data are the business impact and AI use cases. 

Applying human-centered design thinking is a key component to our data and AI projects, because solutions that people want to use will drive high return on investment. Building solutions that are simple and intuitive to the end user are key to driving user adoption. My favorite part of each project is when we demo the solution to our stakeholders, and I get to see their real-time excitement. Data and AI are positioned to transform the future of work.

Describe an interesting project that you have worked on.

Over the years, I’ve worked on many interesting projects. One interesting engagement involved supply chain demand forecasting. Due to changes in market conditions, the product demand forecast was no longer accurate, and this made it difficult to procure the correct amount of inventory.

Data and AI enable us to solve complex business issues, and I am very excited to be part of this transformation journey.

Our team analyzed the business processes, modeled assumptions, and developed a framework to monitor key performance indicators. We developed data pipelines that transformed information from multiple sources and automated processes that historically required manual involvement. Next, we benchmarked various time series forecast models and engineered key features that were relevant to the business. We designed a suite of visualization dashboards that communicate key signals to our stakeholder as soon as they are available.

Data loses its relevance to problems over time, and the faster we can capture, analyze, and act on the data, the more value we bring to our clients. Data and AI enable us to solve complex business issues, and I am very excited to be part of this transformation journey.