The Data Science Consultant’s Guide to a Career in AI
If you’re as chronically online as we are, then you know about the mystery shrouding what a career in consultancy actually means. We can help you figure that out insofar as data science consultancy is involved.
Demand for the specific skill set required for a career in data science consultancy has arguably never been higher. Consultancy giant McKinsey predicts the rise of the data-driven enterprise by 2025, with most employees becoming dependent on data to optimize nearly every aspect of their work. But without the ability to properly manage, analyze and make decisions based on this data, there is little to gain from it.
Broadly speaking, data consultants assist clients by making sure their data is optimally managed; in so doing, consultants analyze data and present their findings in digestible formats for maximum productivity, growth and competitive advantage.
Starting a career in consultancy ensures you’re ahead of the curve: you don’t just see data, you can evaluate the quality of the data, identify potential issues and take the necessary measures and decisions to remedy them. More specifically, what sets this apart from a data scientist position is the way consultants bridge the gap between data and business, translating overwhelming data insights into clear and actionable business plans. These plans entail data consultants’ participation in actualizing strategic data-backed business decisions and presenting those in a way that is client-centric.
If this sounds like something you want to be a part of and work towards, we can get you there!
In this guide, Ahmed Nabih, Head of Services at Synapse Analytics, and Omar Bahig, offer some of the most sought-after answers pertaining to careers in data science consultancy. Let’s take a look!
Which degrees are best suited to work in the field of Data Science Consulting? Can someone from outside of these disciplines work in this department?
Graduates with degrees involving a good deal of problem-solving, analytical thinking, and teamwork are usually best suited for the field of Data Science Consulting. These include degrees such as Engineering (of any kind), Computer Science, Math, Business, Economics, and Finance.
But bear in mind that this list is not exhaustive, as there are multiple degrees that offer similar experiences and we believe there’s always a chance for someone outside these disciplines to work as a data science consultant, given they possess the key required skills (see below for details on this).
Which jobs could an Engineering, Computer Science or Business/Finance graduate apply themselves to in the field of data science and AI?
A company’s department of data science consultancy intimately overlaps with its data science and business development departments. Think about it: in the consultancy arm, you need all the following:
A Data Scientist, who is typically responsible for collecting, analyzing and interpreting structure, unstructured and large amounts of data;
A Machine Learning Engineer, responsible for creating programmes and algorithms that enable machines to take actions without being directed;
A Data Engineer, essentially tasked with developing and transforming data into a format that can be easily analyzed;
Of course, a Data Science Consultant, who ensures optimal data management, analysis and presentation and offers data-backed consultative guidance to clients;
A Data Management Consultant, who is expected to maintain an organization’s budget and oversee deadlines to ensure a structured analysis of the data gathered and, additionally, oversee mainframe security;
Finally, for Data Science Business Development, usually comprising professionals with a data science background who can leverage data in order to enhance client relations, employee productivity, and business performance with technological solutions.
Of course, many of those positions overlap depending on the organizational structure, but better comprehensive than sorry.
What are the required primary skills for someone to work and excel in data science consulting? What are the preferred secondary skills?
The way we see it, you can divide the necessary skills into two parts.
The first part pertains to the technical skills that will help you gain a deeper understanding of the field. These include a fair knowledge of coding languages (it’s always good to have some experience with Python/R Programming), analytics, databases and data management, as well as some knowledge as to building your own models and algorithms.
Some experience working with databases, data visualization tools, and statistics is certainly a plus. Critical thinking and problem-solving, as well as quantitative skills, especially in the realm of statistics and the use of Excel are also key.
The second part involves business skills. It’s a good idea to have knowledge of business fundamentals (domain and field experience). In the absence of hands-on experience, one can take part in academic studies or even online courses introducing prospective students to topics such as management, taxes, or accounting.
Last but not least: some of the key preferred competencies include communication, conflict and time management, resourcefulness, and the ability to work in a team. Soft skills are important!
What advice do you have for graduates outside of this department’s field of expertise who wish to apply themselves to data science consulting?
Case studies, case studies, case studies: you have to complete as many of them as possible!
You can do this in the field of traditional consulting alongside studying beginner-level data science and AI courses. At the same time, make sure you stay up to date on the latest trends and technologies in the field,
and maintain an open and inquisitive attitude.
What do hiring managers in data science consulting look out for in applicant CVs?
Candidates with any data science or consulting experience in a business environment are likely to stand out amongst applicants. For me, previous heavy client-interfacing and project management experience are also a big plus.
What makes a data science consulting graduate stand out in an interview?
A data science consulting candidate will stand out if they are able to communicate effectively and exhibit quick analytical thinking. Their ability to navigate tension as well as good meeting etiquette are also indicators of someone who will likely succeed in the interview.
This guide was brought to you by:
Ahmed Nabih, Head of Services at Synapse Analytics. Ahmed has a B.A.Sc in Mechanical Engineering, which has assisted him in leading over 30 projects at Synapse Analytics, across 10+ industries, and successfully managing all of its clients.
Omar Bahig, Data Science Consultant at Synapse Analytics. Omar graduated with a Bachelors in Electronic Engineering. After starting his career as a hardware engineer, he shifted to the field of Data Science and AI and has been at Synapse Analytics since April 2022.