Q & A with Jane Yu, digital architect for Microsoft Corporation
Data science is a broad discipline with several possible professional paths, depending on an individual’s interests and experience. There are also rewarding careers that require data science expertise without serving as a traditional data scientist.
Jane Yu, M.D., Ph.D., is a solutions architect for Microsoft Corporation specializing in IT systems for data science, AI, and machine learning. She works directly with customers to design and implement IT systems—including data science platforms—that help them achieve their business and research goals. Her job requires remaining current on the latest developments in tech and understanding how tech can improve an organization’s day-to-day operations.
Can you briefly explain your role?
Solution architects are technical specialists who have a good understanding of a vendor’s IT applications and services, as well as their client’s industry, business operations, desired outcomes, and IT workflows. This combined knowledge of IT and business relevance makes the solution architect a critical part of an IT solution development team. Their understanding of the functional capabilities imparted by IT applications and services, coupled with a deep understanding of client workflows and business objectives, ensures that IT solutions that are implemented will appropriately address the needs and objectives of business end users. Without a solution architect, IT teams are at risk of developing solutions that may have impressive functional capabilities, yet fail to integrate well into end user workflows and business operations, thereby resulting in limited adoption.
What do you like most about your job?
My job makes it possible for me to work directly with customers to design and implement IT systems—including data science platforms–that help them achieve their goals. The job gives me the time to stay up-to-speed on the latest technologies that could potentially help my customers. It’s the perfect role for someone like me who enjoys learning about the latest technology, while working with people on solutions development that help make their day-to-day lives easier.
What typical data science skills or models do you employ?
I specialize in the design of high-performance data analytics platforms. This role requires a high-level understanding of advanced analytics, and how these workflows can help my clients achieve their goals. Descriptive statistics and predictive models (e. g., traditional regression-based machine learning) only scratch the surface of the data science capabilities that must be addressed as part of my work. To ensure that I can continually support some of the brightest data scientists wherever they reside, I need to stay up-to-speed on the latest techniques in deep learning, natural language processing, image processing, and scientific/engineering computing.
How do you see the solution architect role changing in the future?
I do not see the solution architect role changing per se. What will likely change is the scope of the solution architect’s knowledge base, which must continually evolve to address emerging IT solutions and mathematical approaches that are becoming available to solve customer challenges. Quantum computing is one such example: currently, there is a lot of scientific interest and investment in quantum computing; however, as of today, quantum computing has mostly remained in the research realm and has seen limited commercial applications. As Quantum Computing and its relevant applications become more mainstream, the knowledge base of the solution architect will need to grow to reflect this.