Job Placement · Technology · Data Scientist
BLS puts data scientists at a $120,230 median, with the bottom decile under $67,240 and the top above $199,130. A single title covering a 2.96x earnings range is a category rather than a job, and it is growing 35 percent to 2035. BEG scopes the point inside that band and places permanently at $12,864 to $15,437 on milestone billing.
Data Science Grows 35%, and So Does the Fee
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TL;DR
Data science hiring goes wrong at the definition, not the search. The federal occupation runs from under $67,240 to above $199,130, covers business intelligence work and machine learning research under one code, and is projected to add 95,400 positions by 2035. On top of that, the median moves $33,590 depending on which industry is employing. BEG fixes the point inside the band, the industry benchmark and the readiness of your data before sourcing, then places permanently at $12,864 to $15,437 rather than the $24,046 to $30,058 a percentage fee would cost at median.
What The Occupation Data Shows
Because the occupation code covers several genuinely different jobs, the earnings band inside it is nearly threefold, and the employing industry shifts the median by more than thirty thousand dollars.
Scope Before Sourcing
Four conditions. Three of them are about your data rather than the candidate, and they are the reason good data science hires leave inside a year.
| Condition | How to test it honestly | What happens if it is not true |
|---|---|---|
| The data is reachable | Can somebody other than one person pull a clean extract this week without asking engineering for a favour. | You have hired a $120,000 pipeline builder. They will do it, resent it, and take the next offer that involves modelling. |
| A decision is waiting on the answer | Name the decision, the person who makes it, and what they would do differently under two possible findings. | Excellent analysis nobody reads. This is the most common quiet failure and it looks like a performance problem when it is a mandate problem. |
| The seat is a scientist, not an engineer or an analyst | Check the duties against the O*NET profile for SOC 15-2051, which files business intelligence analysts under the same code. | You advertise at one pay band and interview for another. Candidates notice within twenty minutes and read it as disorganisation. |
| The degree requirement matches the work | Ask whether any output in the next two years needs original research rather than applied method. | A mandatory doctorate on applied work cuts the qualified pool sharply and adds nothing, while a graduate degree stated as preferred costs you nothing. |
BEG will tell you when the honest answer is that the seat is an analyst or an engineer, because a search opened against the wrong definition wastes your quarter as well as our time. The adjacent titles are covered at data analyst and software engineer. Full scope on the technology placement service page.
Milestone Billing Against A Percentage Of Salary
A contingency firm charges a share of first-year salary. At the $120,230 BLS median for data scientists, 20 percent is $24,046 and 25 percent is $30,058. Benchmark instead against the $142,240 publishing and content median and those same percentages become $28,448 and $35,560. BEG prices this seat as a Tier III engagement at $12,864 to $15,437, fixed before sourcing and unchanged by the industry benchmark you land on or the counteroffer you have to beat. At median that is roughly $11,200 to $17,200 less, and nobody involved in the search is paid more for talking you upward.
What An Unfilled Data Seat Actually Costs
The cost of an empty data science seat is not lost output, it is decisions made on instinct that could have been made on evidence. Those do not appear on a ledger, which is why this vacancy is tolerated far longer than an engineering one. Two things are measurable, though. At the $120,230 median, the budgeted and unspent salary is about $2,312 a week. And in an occupation projected to grow 35 percent over the decade, every month of delay is a month in which the shortlist you assembled receives other offers. The second cost is the larger one.
Who Employs The Data Scientist
All three deliver models. They differ on where the understanding of your data lives once the engagement is over, and on whose payroll the person sits.
| Model | Who employs the data scientist | How you pay | Right when |
|---|---|---|---|
| Analytics consultancy | The consultancy | Project fee or retainer, with the deliverable defined up front | You need one specific question answered well and do not intend to build an internal capability around it. |
| Contract or staff augmentation firm | The firm | Hourly or daily rate plus margin, for the length of the engagement | A fixed piece of modelling work has an end date, and nobody internally will need to maintain it afterwards. |
| BEG permanent placement | You | Tier III milestone fee of $12,864 to $15,437, fixed before sourcing | The models need maintaining, the data understanding needs to compound, and the seat is permanent headcount. |
BEG does not employ data scientists, does not sell project work and is not a staffing agency, so a consultancy engagement is not an alternative we can offer. It is genuinely the right answer for some one-off questions, and saying so early is cheaper for you than a search that should not have opened. Related seat: engineering manager recruiting.
FAQ
A data scientist is a Tier III search at $12,864 to $15,437, billed against agreed milestones. Benchmarked to the $120,230 BLS median for the occupation, a 20 to 25 percent contingency fee on the same permanent hire would be $24,046 to $30,058, rising with every dollar added to close the candidate.
Nearly threefold. BLS reports a $120,230 median for data scientists with the lowest 10 percent under $67,240 and the highest 10 percent above $199,130. A title that spans a 2.96x range is not a job description, it is a category, and the offer you write has to name a point inside it.
BLS projects data scientist employment to grow 35 percent from 2025 to 2035, from 275,600 to 371,000, an increase of 95,400 positions with about 24,800 openings a year. That is roughly twelve times the 3 percent average projected across all occupations, which is why counteroffers on this seat arrive quickly.
Substantially. BLS puts the May 2025 median for data scientists at $142,240 in publishing, broadcasting and content providers, $132,380 in computer systems design, $129,490 in credit intermediation, $128,050 in management of companies and $108,650 in insurance carriers. That is a $33,590 spread by employer type, before seniority enters the conversation.
Only if the work genuinely requires original research. BLS describes the typical entry-level requirement as a bachelor’s degree in mathematics, statistics, computer science or a related field, with some employers preferring or requiring a graduate degree. Making a doctorate mandatory for dashboard and experimentation work removes most of the qualified market for no gain.
No. A staffing or consultancy firm employs the data scientist and bills you for their time while they are assigned to you, and the models they build leave with them. BEG places a permanent data scientist onto your payroll, employed by you, so the institutional knowledge about your data stays in the building.
The occupational definition covers determining which data are available and useful, cleaning and structuring raw data, creating and validating algorithms and models, presenting findings through visualisation, and making business recommendations from the analysis. If your req is only the last two of those, you are describing an analyst and should price it as one.
Most often because the data was not ready. A scientist hired to build models who spends nine months writing extraction pipelines will leave, and they will leave correctly. The honest test before opening the search is whether a pipeline exists that somebody other than one person can run.
Federally, yes, which is a real source of confusion. O*NET files business intelligence analysts and clinical data managers as specialisations under the same SOC 15-2051 code as data scientists. The federal category is broader than the market meaning of the title, so wage data for the occupation covers work that is paid very differently.
23 to 35 days from discovery call to signed offer on average, based on isolved placement data, with an 86 percent fill rate on active searches. The step that most often adds time is an internal debate about whether the seat is a scientist, an engineer or an analyst, which is worth settling before sourcing rather than after.
Give them a messy extract of your own data with no instructions beyond a business question, and score how they interrogate it. What they ask about the collection method matters more than the model they reach for. A take-home Kaggle-style exercise measures the one part of the job that is already well automated.
A 45-day replacement guarantee and 50 percent off a repeat search for the same seat. The candid note is that in a market growing 35 percent over a decade, a replacement search is easier to run than a retention conversation is to avoid. Pay review at twelve months matters more here than in slower-growing occupations.
Building the data function? See data analyst, mid-level software engineer, director of engineering and CTO and CIO, or all technology placement.
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