Many data scientists dream of working in consulting. And I can confirm that it is an exciting job.
Consulting gives a unique chance to see many different companies, industries, functional areas and work with the client side-by-side. Consultants are hired for doing new analyses such that you can work on projects where fresh ideas are needed. You work in teams and a network of great talents and experts, and you can gain extraordinary knowledge of many fields in no time. You travel to cool places and enjoy the team’s social events. And finally, when you decide to leave the consulting business, you will find excellent jobs at your clients.
The consulting job makes you feel important.
I started my career as an analyst and progressed my career to partner in global leading consulting firms. I worked in several different countries and a couple of industries. When I started as an analyst, my goal was to stay two to three years, then looking for a good position at one of our clients and move there. But these three years became five years, the five years became ten years, and finally, it became 15 years. Also, in my current position, strategic consulting is still part of my job.
So, let’s have a look where your dream can become true.
There is not one consulting firm or one role. On the contrary, it is a fragmented market, and each consulting firm has its own focus and strength, and the data science tasks should support that mission.
To shed some light on the different consulting job opportunities and what you can expect, I structure the text as follows.
- What are your data science consulting tasks?
- How to start a career as a data science consultant?
- Where can you find consulting jobs for data scientists?
What are your data science consulting tasks?
Data science needs specialized skills. Not only technically and method-wise, but especially for all the tasks beyond analytics algorithms. Conducting a data science project on a corporate level requires project and stakeholder management skills, literacy of technical infrastructure, and strategic and financial management knowledge.
These are unique skills that not many companies possess themselves.
Decisions had always been made, at least partially, on analytics. Motivated by the tech companies’ success, today, data-driven decisions and business models are the focus of companies. So, they need resources and experienced people to support them in this development.
That is not only on the agenda of large corporates. All companies want to use the benefits of data-driven decisions and business. Every company needs to generate revenues and wants to grow. They have a strategy that reflects the goals and is tailored to the market situation. With the rise of technology and data, the corporate’s strategy typically reflects this shift, and they need data people.
While small and middle-sized companies have neither the capacity and the knowledge to build a data science team, they also do not need a large data science team with several specialized 100% roles. So, they borrow the knowledge and capacities only as necessary.
Larger organizations, on the other side, are often complex structured. Where to start with data science projects? Where do they have the most significant potential for a successful transformation into a data-driven business? Besides the transfer of experience to build that up, they need people who can start doing this transformation without interrupting the ongoing business.
Lastly, having technical and science-based people needs a cultural change in many companies and an explicit integration scheme.
You can see that successfully using data science to drive decisions and products needs a wide range of specialized knowledge and skills. The demand for support ranges from
- Consulting about data science, AI, and data strategy
- Project and stakeholder management in data science transformations
- Showing proofs of value to use complex methods and infrastructures in specific business areas
- Use cases for the company, i.e., where to apply data science with a positive return on investment
- Organizational structure how to embed data scientists
- Cultural change to a data-driven mindset
- Support in building up a data science team
- Train and educate the customer’s teams
- People that can apply data science methods and are knowledgeable about the tools
- Getting the corporate’s data ready into the IT system to analyze them and be able to scale them
- Integration into the business decision workflow and business processes
- Advice in using which technologies, infrastructures, platforms, and tools and deploy them in the company
- Build up and deploy technology and data and IT architectures to perform data science
- Talents that perform the data science tasks
So, consulting firms or departments are centrally trained people to the latest skills needed. They provide the required knowledge, capacity, and skilled experts where required and ensure the company’s business continuity.
How to start a career as a data science consultant?
Traditionally, a consulting career path was set up that you start as a junior, work for many years successful through many different projects and clients, and progress level by level to a manager. And usually, after ten years or more, you make partner. With the shift to technology and data-driven consulting, this career path is diluted. Today, they hire many data and IT-skilled people on all levels. Knowing business administration is not anymore a must, and nerds are welcome. And with this opening, the work and tasks became broader and more technical.
Examples for entering a consulting firm with various backgrounds are:
- Graduate or (self-taught) rookie data scientist: start as a junior data scientist in any consulting firm
- Senior data engineer: join as a manager or senior manager in a technology implementation focused consulting firm for data platform projects
- Business analyst with mainly theoretical data science knowledge: entering as a junior or senior in a data analytics strategy team
- Senior data scientist: start as a manager or senior manager (project lead) for data science in any consulting firm
- Solution architect: join as a (lead) solution architect in a technology implementation focused consultancy company
- Data analyst with data science basic knowledge: start either as a junior data scientist or junior in a data analytics strategy team
Today, there are many opportunities to join a consulting firm from many different backgrounds. The skills are scarce, and the firms compete for these people. Many of these firms also offer internships.
Where can you find consulting jobs for data scientists?
Data science consulting roles are widespread. Strategy and management consulting firms jumped into data science. Technology firms have integrated it for longer. For years, data analytics had also been for years in the DNA of the Big Four developed for their audit work. But also, the local market, niche boutique, and special industry-focused consultancies need data scientists.
Meanwhile, there are focused analytics and Big Data consulting firms and platform providers offering integrated consulting services. Each corporate has today an in-house consulting department with data scientists. And finally, many startups integrate data science algorithms and their results into their products and offer data science consulting as an integrated part of the product.
I have classified them into nine segments and give a flavor of what you can expect.
Disclaimer: The provided Consulting firm’s list is not comprehensive and should be seen as examples for the various segments. There are many excellent consulting firms with particular market or industry focus and specific strengths. They provide many opportunities for data scientists that should be considered.
1. McKinsey, BCG, and Bain (called MBB)
McKinsey, Boston Consulting Group (BCG), and Bain jumped to Data Analytics and data science, too. While McKinsey with Quantum Black and BCG with BCG Gamma have their own digitalization unit with data scientists, Bain has fully integrated them into their strategy consulting teams.
Roughly speaking, there are two types of jobs for data scientists. One is doing technical data science work, i.e., building applications, and the other is in performing data science strategy consulting.
These projects contain task like helping to set up a company’s strategy regarding data analytics, conducting a proof of value where you analyze the value of the (proposed) solution for the organization, set up the roadmap, the organizational structure, and what is needed to set up a Data Science practice (talents, technology).
2. Big Four
Deloitte, EY, KPMG, and PWC are called the Big Four. Their business consists of providing external audit services, management consulting, strategy consulting, legal and tax advisory, forensic services, and corporate finance and acquisition transaction services.
Data scientists are integrated into all these areas. In the external audit area, the focus is on developing and applying tools to support financial data auditing. An example would be to analyze bookings in an account and if there could be potential fraud.
In management consulting, the tasks range from developing analytics pilots for the various industries to support directly in client teams to technical implementation, mainly with providers like SAP or Salesforce.
In forensic services, data scientists support many data preparing and doing analytics to identify fraud cases.
Similar tasks are contained in corporate finance and transaction services but to evaluate companies.
It is important to clarify in what service area your data science job is.
3. Technology consultancy
The most known technology consultancies are (in alphabetical order) Accenture, Capco, Capgemini, Cognizant, DXC Technologies, IBM, Infosys, Tata Consultancy Services, and Wipro.
They offer so-called end-to-end technology consulting, implementation, and outsourcing. That means they support their clients with strategy or management consulting and implement data platforms and IT systems, machine learning algorithms and are an outsourcing provider for these services.
So, your tasks depend on your background and for what position you have been hired. As seen above, it can be strategy consulting, machine learning, data engineering with data platforms, software engineering, or architecture design. And you will meet many technical nerds there.
4. Consulting boutiques and consultancies with local market focus
Many consulting firms in the market have a focus similar to the first three segments, but their focus is on only a handful of markets and industries. They are usually referred to as "tier 2 firms", "boutiques," or "local market-focused." There is no definition of these terms, and it just means that they do not belong to the first three mentioned segments.
I do not give names as the list would become too long. Just enter "consulting firms in <your location/country>" in a search engine, and you will get a list of several hundreds of firms.
Many of them are also providing data science consulting. They are usually more familial, and because they are smaller, one has earlier more responsibilities and a broader range of tasks.
Further, you can be more entrepreneurial in building up new consulting areas or data science tools for clients. Not a few partners and senior experts of the large international consulting firms move to smaller ones because of more entrepreneurial freedom.
5. Niche and industry consulting
Niche consulting firms focus on a single industry, a single region, or a single methodology.
Examples of such consultancies are Porsche Consulting (everything related to auto and similar industries), Gallup Consulting (polls, employee engagement survey, personality assessment), Trinity Partners (life science), Willis Towers Watson (risk management, employee-benefits & human resources and actuarial), Putnam Associates (healthcare) or EY-Parthenon (strategy consulting).
Some of them also need data scientists for their projects. When you are interested in becoming an expert in one industry, niche consulting firms are highly recommended.
6. Big Data and Analytics consultancy
There are numerous specialized big data and analytics companies out there. You can find a list of firms from two people firms up to more than 10’000 employees on GoodFirms.
Not all of the needed talents are data scientists, but many. The range of services is broad, from specializing in certain approaches, technology, platforms, client-basis, or industry to generalist services. When choosing a big data and analytics company, clarify the focus of their business and your work diligently.
If the technology and technical approach are more critical for you than any industry, client-basis, and non-data science related focus, chose one of these consulting firms.
7. Platform and Software providers
All data platforms and software providers have their own consulting business. Examples of well-known companies – in alphabetical order – are: Alteryx, Amazon, Cloudera, Databricks, Dataiku, Dell EMC, Google, HP, IBM, Microsoft, Oracle, Palantir Technologies, SAP, SAS, Tableau, TIBCO, VMware, and so on.
The demand is the same as for technology consultancy. And the demand is increasing steadily. Especially, all data science consulting around cloud computing is in very high demand.
If you want to focus on this specific field, a platform provider should be your first choice.
8. Corporate internal consulting
All global corporates have an internal consulting department. It serves as the centralized hub to develop skills and strategy solutions for the company and to support the different departments in the implementation.
And most corporates have data scientists as part of their internal consulting department.
The internal consulting teams have the same role as the external consultants, ranging from data science strategy consulting to prototyping and implementing machine learning algorithms to data engineering or data platform implementation. Not a few external data science consultants join such corporate teams.
9. Startups
Finally, many startups provide consultancy services as part of their product offering, e.g., in circular economy, marketing, deep learning-based risk management for financial services, educational platforms, big data analytics for governments, and so on.
When you have an entrepreneurial flair and would like to shape a new company and service’s success, this should be your first choice.
Next Steps
A quick look at LinkedIn and Indeed shows more than a thousand consulting-related data science jobs in the U.S. as well as in Europe. And the demand is increasing.
Follow the three steps to get into a data science consulting job:
#1 Your focus
We saw above that there are (too) many opportunities, and you must get clarity about your needs:
- Do you prefer large international consultancy groups with traveling and a defined role?
- Or do you want to join a smaller consulting firm with a broader range of tasks and where you can be entrepreneurial?
- Do you want to become an expert in one industry?
- Is your goal to work as a consultant related to a specific platform of software?
- Would you like to work for a corporate?
- Or would you like to experience the startup feeling?
- Do you prefer a specific work location and a local consultancy firm?
Based on this self-assessment, chose two to three segments or locations to focus.
#2 Do research
Getting a job in a consulting firm needs first of all research, and I mean a lot of research:
- Search through all the hundreds of job offers on LinkedIn, Indeed, and the many other job platforms to find out which company is looking for what talents and what jobs resonate with you
- Search through consulting firms’ lists, e.g., My Consulting Offer, and become familiar with what markets and industries they work, and again, what resonates for you
- Look at Glassdoor or Indeed for employer ratings and read the comments
I recommend this extensive search exercise that you can find a consulting job that you like. I had several hires who resigned again after two to three months throughout my career because it was not the type of consulting they wanted to do. It enhances your success rate of job satisfaction enormously.
#3 Prepare for the hiring
Most important is to know what they expect the qualities you bring into the company. These qualities are technically and your personality.
- Look for people in your network working in consulting and ideally at the one you would like to join. Ask them about the culture, and work. Ask them to put you in contact with people working in the area where you are interested
- Attend public events of consulting firms where you can look at how they work. You meet the people and can ask them your questions
- Look on Quora. Many questions about consulting firms are already answered. If not, you can post your question.
This information is essential. The better you know what they are looking for, the higher the chance you get your dream consulting job.
The start in one segment does not exclude the move to another. I moved between the different segments. Every time I worked diligently and considerably through all three steps and had success.
There are no limitations. You are the sole driver of your career path. And data science consulting is an exciting one.
Disclaimer: I am neither paid by any of these companies nor do I have any current affiliation with them. The companies mentioned serve for the sole purpose of giving examples and not for promotions.
Do you like my story? Here you can find more.
The Top Technology Trends and Their Impact on Data Science, Machine Learning and AI
5 Exciting Industries for a Data Scientist Job Outside of the Tech Sector
The Ultimate Guide on the Data Science MicroMasters Programs on edX 2021
