An overview of the interview process and the benefits
Recently, I was searching for inspiration to better understand what data-driven companies were looking for out of Data Mining/Modeling candidates and came across Dr. Tim Graettinger.
Dr. Tim Graettinger is the founder and President of Discovery Corps, Inc. He is an experienced individual with an exceptional track record of innovation, creativity, and quality. He oversees all aspects of company operation, from sales and marketing to client training and consulting services. Tim also provides leadership and technical direction for the company. (Graettinger, 2020)
In this case, I read one of Dr. Graettinger’s published articles about his interviewing approach with candidates and wanted to share my #goldendatainsights.
I hope my review of Dr. Graettinger’s approach helps you better understand what’s expected from candidates seeking data mining/modeling career placement. In addition, you will also reap the benefit of modeling Dr. Graettinger’s interviewing style and adapting it to your own workplace scenario.
What is your general impression of the article and the author methodology?
After reading Dr. Graettinger’s (2011) philosophy on interviewing candidates for data mining/modeling (DM) positions, it was clear that being a hiring manager in search for unique DM skills isn’t an easy task. But with the right approach, a little preparation, and a list of interested candidates, the interview process for a DM position may not be such a daunting task after all. For instance, let’s take a look at Dr. Graettinger’s approach to interviewing DM candidates.
His primary goal is to find out if a candidate is smart, focused, and compatible (Graettinger, 2001). He facilitates the interview with a structured process that helps guide him and the candidate through a sequence of activities (i.e. Introduction, Recent projects, DM process overview, Troubleshooting, and a Wrap-up). During the activities, a deep dive into scenario based and Why questions are presented by which information/knowledge is collected on the candidate for evaluation purposes. Likewise, information about the hiring company, team, and position are also provided to the candidate to spike their interests. Overall, I think this simple yet structured approach to interviewing DM candidates provide hiring managers a comprehensive way to gauge whether a potential candidate is right for the position and/or the company. Equally impressive, it offers a balanced approach that serves both the candidate (i.e. in their effort to learn more about the company/position) and the company (i.e. in their effort to find the right “fit” candidate). All in all, I like the author’s methodology and plan to personally consider using the structure to prepare for future interviews of my own.
Give examples of situations he described about his interviewing style and tell me what you would do differently.
Dr. Graettinger’s structured approach to interviewing seems like a great starting point for anyone seeking to hire skilled data practitioners. His strategically placed questioning techniques give interviewees (i.e. candidates) the ability to start the interview process with ease-of-stress by engaging in simple small talk. During this introductory phase, Dr. Graettinger says it’s important to outline the structure of the interview with the candidate so they are aware of where they are, where they are going, and how they fit into the bigger picture in terms of the company’s open position (2011). In this case, I really like his approach because I also believe it’s critical that the candidate knows exactly where they fit in the big scheme-of-things and how that aligns with the company’s vision. Additionally, I think it was a wise move to allow the candidates to ask questions before the interview started to allow them to further ease their mind. According to Graettinger (2001), he would usually answer some questions at that point and follow-back with the remaining unanswered inquiries during the end (i.e. wrap-up) of the process. I enjoyed that concept because it helps set the mood (i.e. tone-in-the-room) for the remainder of the interview. For all said reasons, I wouldn’t change a thing about this interview approach and would highly consider using it for personal use.
Furthermore, Dr. Graettinger does a great job collecting relevant information about candidates by using techniques such as asking them to tell a story about a recent DM project. During story time, candidates are evaluated on their ability to communicate, frame problems, describe characters, and express interests on project lifecycle-of-events (Graettinger, 2011). This is a classic in-direct evaluation technique that allows the hiring manager to better understand a variety of variables about the candidate without formally having to ask direct questions. Similarly, Graettinger (2011) highlights the importance to ask WHY questions in order to gain insight into how candidates think and whether or not they are prepared to justify and/or support their decisions. Likewise, I learned about the ‘trio-of-questions’ to use as an assessment tool to evaluate a candidates’ ‘fit’ with the open position. Dr. Graettinger says that by asking candidates to tell him about their favorite part, least favorite part, and most challenging part of their recent DM project, he is able to assess whether the candidate is the right fit for the current opening (2011). “Companies want people who use interactions with others as an opportunity to learn, to engage, and to gain more knowledge” (Graettinger, 2011). Another important question, according to Graettinger, is asking candidates What they learned during the lifecycle of a DM process. This touches home for me because I personally try to use every interaction with others as an opportunity to learn or gain new insight.
Moving on, Dr. Graettinger (2011) explains how asking candidates about the DM process really helps him decide whether they have the skills he’s looking for. As an example, a good answer would be along the lines of, “I used CRISP-DM or SEMMA” (Graettinger, 2011). With this in mind, Dr. Graettinger suggests that even if you have a personal way you like to do business in today’s creative world, it’s more important to understand the proven industry-standard methods that can be used as a solid starting point and later be modified for performance input/output fine-tuning.
Later on, in the interview process, Dr. Graettinger highlights his interests to initiate a discussion with the candidate about troubleshooting. I really like the troubleshooting part of the interview because it allows the candidate to get hands-on exposure to a particular set of data where the candidate can assess the reporting for problems (if any), develop solutions, and plan a strategy to move forward.
To wrap it all up, Dr. Graettinger says that during the final part of his interview process, he answers any hanging questions, pitches the company and its open position, and makes his final thumbs up or down decision about the candidate (2011). For a closer, I think Dr. Graettinger makes a smart move of going back to any hanging questions that the candidate may have asked during the interview and answers them to the best of his knowledge. This helps forge relationships with the potential candidate(s) by the hiring manager acknowledging candidate inquiries and answering them for clarity before finishing the interview.
With all things considered, I wouldn’t change a thing about Dr. Graettinger’s approach to interviewing a DM candidate.
What did you learn about data mining and the interviewing process that you find particularly insightful?
The most insightful thing I learned about data mining after reading about Dr. Graettinger’s interview process is the importance of knowing and using industry-standard tools (i.e. CRISP-DM and SEMMA), methods, and practices when performing DM projects. By using a scientific approach combined with the personal art of intuition and research, results are often accurately generated. When the art approach is used and later layered with a scientific method, results get lost and its often hard to explain outcomes. Basically, stick with the universal method and use your creative expression with it. In addition, as a job-seeking DM candidate, I learned a lot about DM interview questions, terminology, and expectations regarding the importance of DM processes and technologies. As Dr. Graettinger mentioned, being able to tell the story about your DM project and the characters involved is just as important for some positions as knowing how to do the technical aspect of the job (2011).
If you want to learn more about Data Mining, check out some of my other blogs on the topic at the following links:
Discovery Corps, Inc. (DCI) is a leading-edge data visualization, data mining, and predictive analytics consultancy. Founded in 1998, DCI works with clients in a broad spectrum of industries, including life sciences, health care, pharmaceuticals, manufacturing, direct marketing, and financial services, among others. This broad base of experience enables us to translate lessons learned in one domain into inventive solutions for another.
Positive vibes heading your way if your either a job candidate or the actual interviewee. Until next time ya’ll, keep it real!