Exploring the role of a data analyst in the semiconductor industry

Ali Hariri

Can you please provide a general overview of your job?

I started my career as a semiconductor Test Research and Development (R&D) Engineer at Intel. I was responsible for developing and enabling test technologies (hardware and software) for Intel’s latest semiconductor products in order to ensure high standards of quality and reliability while maintaining the feasibility of high-volume manufacturing and cost effectiveness.

Recently I made a career change into a Yield Analyst role. A Yield Analyst is an integration and data analysis role. It requires a broad knowledge of the full manufacturing process flow rather than focused expertise in a single process. In this role we develop data systems and utilize big data from multiple processes in order to identify process issues and provide solutions to improve the factory outputs.

What are some typical day-to-day tasks?

As a data analyst with electrical engineering background, I mainly focus on electrical test data. A typical day starts with scanning through the automated data systems that we develop to track the health of the process flow. I then identify sources of failure and defect modes in the semiconductor packages based on the data. Then I work with failure analysis labs to identify the root-cause of the failure. After identifying the root-cause, I work with process engineers to propose solutions to eliminate the defects. Other day-to-day activities include developing automated data systems to better visualize the data and drive faster conclusions.

In your experience, how common is this type of position in the industry?

Both roles that I have held are very desired in the industry. Any company that has manufacturing factories and R&D sites will need process engineers and data analysts. As companies try to be more competitive and utilize data-drive problem solving, yield analyst roles are becoming more essential.

Many grad students feel that their research projects are too abstract or far from translating into real-world applications. How is the work environment different in the “real world” compared to grad school?

The industry environment is much more fast-paced compared to grad school. Deliverable timelines are more aggressive especially in highly competitive fields. Moreover, the industry environment is more dynamic since you always have to respond and adjust to the latest advancements from competitors. This leads to frequent cancellation of projects and retargeting of roadmaps so we’re constantly adjusting and adapting to such changes.

It’s probably very exciting to see your technical skills transformed into successful market products! How does that affect your work enjoyment and productivity?

It’s definitely very rewarding to see the direct results of your contributions transform into market products that affect people’s lives. This feeling of self fulfilment results in higher productivity and work enjoyment. However, this becomes tricky depending on the type of industry. Many industries have negative impacts on people’s lives and that becomes very discouraging to contribute to. It’s very important to research the company practices before joining it and make sure it’s cohesive with your principles.

At some point before your successful career in industry, you were interested in an academic career. What changed your mind and how do you look back on that decision?

There are a lot of factors that led to my decision to get a career in the industry rather than academia, even though my original intent was to pursue an academic career. Unfortunately, I see many people making a similar decision for the same reasons, and I believe this is causing the academic field to miss out on a lot of talented individuals. 

First, as a non-US citizen, you don’t have many choices after graduation, you need to find a job to maintain your legal status. Many companies use that to their advantage and provide immigration sponsorship to lure in talented researchers. Second, the academic track is not convenient for low income people. A career in academia usually requires a few years of post-doctorate (post-doc) experience. In my opinion, post-doc researchers are underpaid. A post-doc salary is not enough for someone in their late 20s (or early 30s), coming out of grad school, especially if they come from a low-income background with responsibilities to take care of their families, pay off loans, and start an adult life. Third, the academic field is becoming more bureaucratic where it rewards name recognition of the school or lab when applying for grants or in research publication. This favors elite ivy league schools for funding and publication and discourages smart researchers from modest schools and labs.

These are the main conditions that made me favor a career in the industry at that point of my life coming out of graduate school. Overall, I think the industry experience has been very valuable. Looking back on that decision, under those same circumstances, it was the right decision to make.

What are the main skills you learned in grad school that help you be successful at your job?

The most important skill that many graduate students acquire in grad school is how to work independently. Grad students tend to be more independent and require less micromanaging. In grad school you also learn how to research and learn new topics on your own which is a very valuable skill in the industry. Stress management is also a valuable skill that many grad students tend to have compared to undergrads.

What advice would you give to grad students who are interested in similar careers?

First, be ready for a very different environment and mindset than in academia. As mentioned earlier, the industry environment is fast-paced and dynamic. Cost-benefit analysis drives most projects rather than the technical significance of the research itself. Second, ensure that the industry fits your principles. Research the companies and their activities and ensure that it’s a good fit for you. Third, do not be afraid to try new things and learn new topics that may be completely different from your field of expertise in grad school. Starting a career in the industry is like starting grad school all over again. You need to be able to cope with going from a recognized expert in your field of research, to a new employee with a lot to learn when you join the industry. Finally, you should keep in mind that going back to academia after spending time in the industry is possible but is hard depending on the field of research. Eventually as long as you’re fulfilled with your career and you’re contributing positively and learning new things then you’re on the right track.

Dr. Ali Hariri is a Process Yield and Data Analyst at Intel Corporation

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