Client-facing skills for data science consultants: luxury or necessity?
By: Pouyan R. Fard
Tags: Careers, Customer Centricity, Business, Consulting, Data Science

Client-facing skills for data science consultants: luxury or necessity?

What it takes to be successful as a data science consultant

Photo Credit. Fauxels @ Pexels.com

There was a time that I thought you could be a top data science consultant by having excellent core tech skills like machine learning, data analysis, and software engineering. When I started working in my data science consulting job, I was excited to work as a consultant for a known global brand. I was very motivated to put the solutions that I learned through my academic and startup career (with studying papers, reading code repositories, and taking online courses) into practice for very large corporations.

It took me years to become an experienced data science consultant who can work independently in client-facing environments.

But soon, the reality kicked in, and I understood that I was not well equipped with the skills I needed for being a successful data science consultant. It took me years to become an experienced data science consultant who can work independently in client-facing environments. During these transition periods, most of the learnings were when I was facing difficulties in my projects and receiving constructive or critical feedback from my colleagues and superiors. After these learnings, I started to understand how to serve your clients successfully as a data science consultant.

The most crucial type of skill you need, on top of your tech skills, to be a successful data science consultant is your client-facing skills. In a nutshell, there are many client-facing skills, such as active listening, communication, empathy, goal-oriented problem-solving, and dedication. Here, we focus on the most critical one for a data science consulting career that is goal-oriented problem-solving.

A consulting company is mostly a client-facing professional services company, rather than not a product company. Most people in these companies are working on projects developing outsourced solutions, and eventually delivering them to the end clients. While some teams are working on products but working in client-facing environments takes precedence in those companies.

As a newly-hired data science consultant, you may be very passionate about the solutions and technologies you have learned during your education and early career. You might be even very proud of yourself that you work on so many cool technologies, and you should be. You are probably very excited to present the insights that you read in some academic papers or tutorials to other people. You want to apply your learnings from the new online course you took in practice for a big client of yours.

You will soon understand that other people in your projects are in more contact with the clients. Maybe, they are much more senior than you or salespeople. And they may start telling you that the solutions you propose are not the ones that the client wants. Or you are making the solution too complicated. After all, they know more about the actual requirements of the clients comparing to you. And that is the time that you start feeling really under-appreciated or even un-welcome.

You realize that being customer-centric is an essential part of the game in the consulting companies.

And believe me, I understand. You may feel like the consulting industry is not for you, and you have to go and start over. But you need to realize that being customer-centric, i.e., putting the client’s requirements and, by extension, the project stakeholders first, is an essential part of the game in the consulting companies. Most of the time, you need to focus on the ultimate goals the business is trying to achieve in response to their problem; in the end, you solve your clients’ problems, and they don’t know about data science or artificial intelligence. They just want to solve their business problems.

Often in your early consulting career, you offer a too complicated solution for the clients to understand, and even for your superiors to explain. These can be some complex deep learning solution you read in one paper recently and found it interesting. You will soon realize that in most cases, the best solutions are the most straightforward solutions that you can demonstrate their value to the client quickly. Once your solution’s general direction is approved, you can build on top of that with more complex levels up to the needed level.

On top of the solutions you offer, the general professional etiquette you will have as a management consultant is a crucial part of your role as a data science consultant. Remember, if you are working in a large consulting company, your clients hire your company to provide world-class service to them. The clients most likely want to receive top-quality work with a high level of professionalism.

In consulting, the customer is always right.

How you treat your consulting clients must be the best examples of customer-centricity and sticking to the belief that “the customer is always right.” You will need high levels of empathy, dedication, and active listening when serving your clients in a consulting engagement, which is the essence of this business.

In summary, you need to be very practical in approaching the project’s requirements and your problem-solving when working in consulting companies. Also, keep in mind that being a client-facing data science consultant means that you always need to put the needs and requirements from the clients and the project stakeholders above your preferences on how you want to solve this business problem.

About the Author:

Pouyan R. Fard is the Founder & CEO at Fard Consulting & Data Science Circle. Fard Consulting is a Frankfurt-based boutique consulting company serving companies in various industries. Pouyan has years of experience advising companies, from startups to global corporations, on data science, artificial intelligence, and marketing analytics. He has collaborated with Fortune 500 companies in pharma, automotive, aviation, transportation, finance, insurance, human resources, and sales & marketing industries.

Pouyan is also leading the Data Science Circle team to build a career hub between employers and data science talents. DSC’s mission is to nurture the next generation of data scientists through career training and helping the employers to find top talents in big data.

Pouyan has done his Ph.D. research work on predictive modeling of consumer decision making and remains interested in developing state-of-the-art solutions in machine learning and artificial intelligence.