Talent Spotlight Series: Data and Analytics Consultant

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Today we are talking with Quinn MacLean about his career as a Data and Analytics Consultant.


Before we get started, I have to brag on Quinn for just a minute. Over 5 years ago, Quinn was assigned the arduous task of getting me up to speed on all reporting for a team we previously worked on together. (Thanks for your patience, Quinn!) After that task, we both got to work redesigning the reporting capabilities of the department.


The thing that impressed me the most about Quinn was his creativity and drive. Any vision I had for the team he figured out a way to capture it in data. No ask was too complicated! Since that time Quinn has completed a master's degree, changed companies, and has taken his career to the next level. If you ever get the opportunity to work with Quinn - you will have one stellar teammate in your corner!



Now let's learn more about Quinn...


Name: Quinn MacLean


Current Position:

Data and Analytics Consultant at Slalom


Time in Current Position: 4 months


Where Can You Connect with Quinn?


LinkedIn: https://www.linkedin.com/in/quinnmaclean/


Email: qmaclean48@gmail.com


GitHub: https://github.com/qmaclean

(See samples of his work!)



What does a day in the life of a Data and Analytics Consultant look like?


It depends on the project, but typically I am placed at a company as an added resource. My main objective is to provide subject matter expertise and deliver high quality analytics work. The work I deliver ranges from data visualization products (like dashboards and data applications), engineering a table used for analysis, or providing data analysis to drive action for business users.


On top of the client work, I meet regularly with other consultants to trade ideas or learn about a topic they have expertise in. I also work on a lot of sports analytics projects outside of work! (See Github For My Portfolio: https://github.com/qmaclean)


What roles did you have prior to your current role?


I’ve been working in business analytics or data engineering-based roles for close to 8 years now. I’ve been exposed to data/analytics in the following industries: Telecommunications, Financial Services, Banking, Fitness, and Retail.


How did your experience in previous roles help you succeed in your current position?


My previous experience has provided a lot of value as I have had the opportunity to work with individuals of varying backgrounds. Through these experiences I have learned there are 3 themes to success in Data and Analytics: Active Listening, Translating, and Setting Expectations.


In order to excel (ha pun intended!) at data & analytics, you need to get really good at requirements gathering, which basically means understanding the “why” behind someone’s ask. Take as many notes as possible, ask follow up questions, and indicate you understand their ask before you begin a project.


From there you have to translate that information into a solution. It's important to always remember that you will only talk about a portion of the information during requirements gathering. I always remind myself that the average person buys cars or houses on only 20% of known information. It's my job to translate, or fill in the missing information, to make sense of the ask.


Lastly, set expectations as to when you plan to have something completed. This practice provides good customer service and will build trust with the requestor.



Is there any specialty training or area of expertise needed to succeed in your current role?


Working knowledge of the business process and how the data is stored is a majority of where I spend my time. The business process can tell you a lot about what decisions are being made and that can help you decide what to measure.


Believe it or not, most employees have a good amount of unconscious bias in decisions they make day to day. Analytics can help to unearth the bias. Understanding how data is stored begins the process of transforming, or wrangling the data, to a format that will help you explore how well a process is performing. Knowledge of statistics and data transformation programs (SQL or Python) is helpful as well.


How do you think your job will change in the next 5 years?


From an industry standpoint, Data and Analytics typically lags behind practices and behaviors we see in Software Engineering. I also anticipate data & analytics will start to replicate DevOps principles adopted by Software teams as a way to improve overall workflow.


Another trend I can see on the horizon is specialization within data teams. You’ll likely see more companies adopting an approach to have people who build data tables and those who interpret and present information from those tables.


What parts of your job do you find most challenging?


Being data driven is a disciplined approach that breeds good decision making. However, being data driven doesn’t always mean that you are going to have 100% positive outcomes from those decisions. It just means that you are more probable to have a positive outcome.


A challenge I face working in this space is from individuals finding results in the data to justify their initial decisions. Usually bad decisions come from bad assumptions. I typically advise clients to spend more effort ignoring bad outcomes and instead focus on measuring the results of their assumptions to drive change.


I also find Imposter Syndrome to be a challenge in the consulting field. As a consultant, you are challenged to be up to speed and providing expertise quickly within an organization. That means learning all of the corporate jargon, systems, background context, key stakeholders, systems, putting in access requests, and much more. This is a recipe for imposter syndrome to creep in.


I find a way to combat imposter syndrome is to take a lot of notes, ask a lot of questions, use your consulting network, and smile! It’s okay not to know everything. I always try to remain confident in my skillset even if I don’t know all the specifics. I’ve been programming for a while now and I still am re-looking up snippets of code even though I’ve used it plenty of times before. I’ve found many programmers are the same.


What parts of your job are most rewarding?


I love solving problems. It’s the biggest reason I’ve stayed in this career field. Being able to transform and uncover insights has led to so many ah ha! moments in my life.


I’ve gotten the most adrenaline, motivation, and learning on having some sort of constraint (time, technology, additional help) placed on me while attempting to solving a problem. That’s a big reason why I got into data & analytics and consulting, you are unlocking an opportunity (aka problem) that others view as a burden because the constraint is something they don’t want to work around.


Are there any professional journals/organizations/etc. that someone interested in this field should be aware of?


I’ve found myself coming back to articles featured on “Towards Data Science” or other medium based analytics articles.


GitHub has a lot of cool public projects that people have built and you can easily copy down someone’s repo to learn more (I do this often). I draw a ton of inspiration from sports analytics to use in my work.


What other paths can I take in this field?


The great part about analytics consulting is you get introduced to a variety of companies, industries, technologies and ways of working. You are also constantly up-skilled on modern approaches and technologies as way to deliver value to your clients. Because of this, it is fairly common for people to leave consulting to work for companies that meet their perfect job criteria.


On the other hand, people gravitate to consulting because they work solely on projects and are not entrenched within a company’s culture. It’s fairly common for people to move in and out of consulting and it isn’t viewed negatively by the industry.


How many hours do you work in a typical work week?


I work 40 - 45 hours in a given week.


The number of hours you work is dependent on your client, project, your level of involvement in consulting community, and your time spent learning. Given your work is billed to a client, you typically don't need to work an excessive number of hours (unless the client is expecting you to due to deliver a project by a quick deadline). The number of hours I’m required to work is usually predefined by the project so I have an expectation going in.

 

If you are interested in learning more about Quinn and his experience, please feel free to connect with him on LinkedIn, send him a message through email, or follow his work on GitHub. There are direct links at the top of the blog!


If you would like to be featured on the Talent Spotlight Series, please contact me here!

I would love to share your career journey!



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