What sort of projects do DS consultants do?

It really does vary, but oftentimes it's inside of other larger projects (software projects etc) where data science is a component of that project.

For example, setting up a recommendation system for products is generally a step on the end of setting an MDM (master data management) system or a data warehouse. It pays to be aware of how these more traditional types of data projects influence the data science space as often they go hand in hand.

There are of course a lot of POC (proof of concept) projects which are smaller scale, 4-6 week projects that focus on validating a concept at a small scale before moving ahead with a larger project. This may involve demoing capability of a certain tech stack, or building a quick model to show that there is potential. For example, you may be given a use case to test like ‘build a model that shows the effect of x on y’, in that 4-6 week period you would build a project that assesses the validation and business value of that proposition and if it suits being made into a full project.

There is also workshopping, strategy work, and teaching internal client teams.

How does a consultant differ from an employee? Why do companies hire you?

It's the process and interaction surrounding the actual work that differs the most. Consultants are also required to wear a lot of different hats from time to time, from architecting implementations, to setting them up, building, testing, iterating, documenting, to teaching client resources for a handover, and even sometimes building models!. Then on top of that, consistent stakeholder feedback, understand what the client actually wants out the project, explaining concepts, pre-sales pitching of ideas and concepts.

The main differences are around the more general understanding of business fit & application, and the ability to fit your ideas and projects in a way that suits the client and what they understand.

In consulting there is rarely a chain of command telling you exactly what to do, giving you 20 weeks to do it, and then reporting your progress when you're done. It’s much more involved and consultative within the process itself. This essentially means that hiring a consultant you are not just getting a predefined project built, you are paying to get the experience, business knowledge/understanding, to define and build a project that suits your business.

There is also an interesting phenomenon that tends to happen where after some initial pushback, internal teams work well with consultants and consultants can generally get results internal to a business quicker than people within that business can as your outside of the normal business framework it allows a lot more flexibility.

What can people expect to earn and how they should charge for their services?

It’s hard to pick a specific rate because it really depends on what your doing and the perceived value of the projects you are undertaking. Are you providing something no-one else (in the vicinity) can provide? Then your project/rate should reflect that, never undersell a skill that's hard to find.

What's an example of a project you worked on?

A good example of this is a project I was brought into to determine the roadmap (design the strategy, what tech to use, machine learning pipeline, etc.) it was a 2.5 week project which required looking and understanding their data by meeting with SME’s (subject matter experts) and determining exactly what needed to be done to the data to achieve their goal (which was to identify & predict customer pain points with billing data).

From this I designed the solution and the roadmap and wrote out how their internal team would design it. I also was brought in a few more times on the project to validate and check their work, as it was not only used to build a good project but train up their internal resources for the work which was a great way to approach it.

On this project I was on a rate of $2000 AUD a day, for the 2.5 week period which was inclusive of further recommendations later on (which totalled no more than 4-5 hours). For a top-shelf data science consultant with the ability to explain to and understand stakeholders, as well as architect and design large-scale data science projects with a considerable background can fetch AUD $2500+ per day, with more niche skills clocking in higher than that still. With most rates coming around $1600 - $1900 per day for contract work.

However, the more effective way of charging is to charge based on the project as this accounts for all costs and its inclusive of the wage, and oftentimes the margins will be higher on these types of projects.

Do you outsource any of the work?

It depends on the nature of the work being done, the team I work within has scope for a majority of the facets of data science (and sometimes near enough that we can figure it out) but when there are obvious gaps we generally try to contract trusted people and failing that we use outsourcing. When using both contracts and outsourcing, its a good idea to do the architecture and overall integration design yourself ahead of time, not only to provide clarity but to make sure that what you're after in context can be delivered by the resource. Outsourcing can be good if the resource is trustworthy, but it also has to be factored into the larger project at hand if the development style and knowledge of the person undertaking the work fits into the overall picture. For example, if you serve models in docker images, yet a resource doesn't understand that method, does it still work in your architecture?