What do you charge? This is a tough question to answer unless you’ve seen a lot of consulting rate cards. I have so strap in.
First, I need to dispel the myths. Upwork. Yes, there are Data Scientists on the platform who advertise their services for $30-$70 an hour.
There are several problems here. However, I’m not going to say anything disparaging about people who post services on boards like these. Many are awesome talented Data Scientists who have chosen to deeply discount their rates below market value. Suffice to say, this is not who you’ll be competing with, so don’t price yourself based on their rates.
Next, salary surveys. Their methodologies are flawed. BLS lists Data Scientists with other Mathematical Science jobs and that greatly lowers the salary averages. Job boards are skewed towards employers and reliant on questionably gathered survey data.
Many people who post their own rate ranges are amazing resources. Unfortunately, they’re all over the experience spectrum and you need the big picture to price correctly.
For all those reasons, it’s important to understand how consulting companies set the market price for Data Science consultants so you can set a competitive rate.
I am going to break this down into 3 roles: Data Scientist, Data Engineer, and Machine Learning Engineer.
Consulting houses create tiers for their consultants. It’s a Level 1 - 5 scale that allows them to charge more for top tier consultants. How do they differentiate between the tiers?
Years of experience. Usually this is the breakdown:Level 1 = 1 yearLevel 2 = 3 yearsLevel 3 = 5 yearsLevel 4 = 7 yearsLevel 5 = 12+ years
They also give them titles and that’s where things begin to get a bit confusing, so I am going to simplify it all. However, I want to give you some insight into the game.
What else goes into the pricing sauce? Degree is a big deal in Data Science. A PhD can substitute for years in many cases. Some companies take a Data Scientist with a PhD and 1 year of experience and rank them in the Level 3 – 4 categories.
Scope of responsibilities creates an alternate structure. Companies have Subject Matter Experts where top talent does Data Science work but because of an exceptional pedigree or body of work, they are capable of taking on the most advanced projects. They also command a much higher rate.
Some consultants are technical leads or project leads and do Data Science work as well. That is another alternate structure which bumps the rate up.
Putting Yourself In The Right Tier
Personally, I price myself in 2 different tiers depending on the type of project. You may find yourself in a similar boat. You can probably do Data Engineering and Data Science or Data Engineering and Machine Learning Engineering. You’ll have 2 different rates depending on the type of project you’re brought in for. I have a strategy and SME rate. Think about doing the same to help potential clients see your ability to take on the full range of projects you’re capable of completing.
Compare yourself to others in the field. Machine Learning Engineering is relatively new. Having 5 years of experience puts you at the top of the range so you’d be a Level 4 or 5 rather than a 3.
Also include experience you may have brought into the job from another role or field. 5 years as a Data Analyst and 3 years as a Data Scientist should put you at a Level 3 rather than 2. Many companies have a concept of experience equivalence where experience from another role can be translated into a higher level.
Your previous job title and company play into the prestige game and consulting is a very prestige driven profession. Ex-Google or Facebook is a big deal and will put you into a different tier or even an alternate structure.
Deciding The Dollar Amount
Now that you’re in the right tier and structure, the explanation of rates will make a lot more sense. Data Science consultants Level 2 – 4 make between $200 - $300 per hour. Machine Learning Engineer consultants Level 2 – 4 make between $225 and $275 per hour. Data Engineer consultants Level 2 – 4 make between $175 and $300 per hour.
Data Engineers are often lumped in with other jobs so for some projects they are on a lower structure. In other cases, they are more like Data Scientists and get the top end of the scale.
Realize that you are competing with large companies who charge their clients those amounts. If you don’t have a standout background or track record, you’ll need to compete on price or you’ll have a hard time getting work. My rule of thumb is drop 25% off those rates and you’ll be in a good range.
If you’re in the Level 5 or a higher alternate structure, going over $300 per hour will not raise any eyebrows. How high? As high as a customer is willing to pay. It’s difficult to gauge how much more you can charge once you get above the $300 hourly rate. Most customers cannot afford you and so you limit the total pool of interested companies.
However, an odd thing happens when you start charging a lot. Those companies who can afford you have a higher perception of your capabilities because you charge so much. If you have large, profitable project success to back up your rates, going high is not a bad thing.
Client Size Matters
At a large company, over $1B in annual revenue, charging the full rate for your range is fine. However, smaller companies will not be able to afford that rate. You will want to take business size into account when you quote a price. Especially at early-stage startups, you may take a massive decrease to land their business.
Is it worth it? Depends on how booked up you are. Consultants don’t all run at 100%. I’ll usually take on enough strategy consulting work to keep me 40% - 50% booked. I will sometimes take smaller clients at a lower rate to fill in hours. I cherry pick projects that are interesting to me or that will look good in my body of work.
The strategy of filling your schedule with part time, high priced hours then supplementing with some lower priced hours has worked well for me and it’s worth considering. Having a good mix of clients also keeps you safe from losing one and scrambling to get money coming back in the door again. It’s easier to search for a replacement when there’s a steady stream from other clients to fall back on.
The biggest takeaway should be, don’t race to the bottom on your rate. There are so many companies bringing in consultants that it doesn’t make sense. Set a rate that you can justify with your education, years of experience, and achievements. The real secret is knowing how to market yourself when you send out your rate card. Make sure there’s a paragraph or 2 justifying your rate using the framework I’ve outlined.