Data Science Jobs Pay Across LATAM in 2026
In 2025, average pay for engineers and data scientists combined sat near $67,000 in Brazil, $48,000 in Mexico, and $42,000 in Argentina, while the May 2025 U.S. median for data scientists was $120,230. Treat that U.S. figure as a remote reference, not as the salary a local contract in São Paulo, Mexico City, or Buenos Aires will pay.
The gap between those rows is what data science jobs pay turns on in 2026. A candidate in Córdoba or Recife often gains more by changing who signs the paycheck than by moving from junior to senior inside one city. A bank in Mexico City and a U.S. product team hiring from Medellín are not pricing the same market, even when the title matches.
LATOjobs readers in Argentina, Brazil, Mexico, Colombia, Chile, and Peru need two anchors before a recruiter call: the local country figure, and a rule for when an international payer should sit above it. What follows separates surveyed averages from teaching examples, then shows how to screen listings and negotiate without treating a headline mean as an offer.
Data Science Pay by Country in 2026
A 2025 compensation report cited by G1, drawing on more than one million contracts across 150 countries, placed average annual compensation for Brazilian engineers and data scientists at about $67,000. The same comparison put Mexico near $48,000 and Argentina near $42,000. These are directional anchors, not guaranteed offers. The source mixes engineers with data scientists and blends seniority, specialty, and contract type.
Converted figures in that report were roughly R$358,900 a year for Brazil, R$273,000 for Mexico, and R$239,000 for Argentina. Exchange rates and contract structure move those local-currency values, so cross-border talks are safer in USD than in pesos or reais.
The U.S. Bureau of Labor Statistics occupational outlook reported a median annual wage of $120,230 for data scientists in May 2025, about $57.80 an hour. That belongs in the same view as an international reference. It isn't a LATAM local salary, and it covers data scientists only, not the mixed engineer-and-scientist average used for the three countries.
Country rows, not city rankings
The report stays at country level. It doesn't split São Paulo from the rest of Brazil, Mexico City from Monterrey, or Buenos Aires from Córdoba, so don't rank those cities as if the averages proved a city premium.
Chile, Colombia, and Peru sit outside this comparison. There's no verified figure for them here. Use the closest anchor as a starting point, then ask the recruiter for the band before you treat any number as yours.
MarketAnnual figureLocal noteWhat the figure coversBrazilAbout $67,000Roughly R$358,9002025 average for engineers and data scientists combinedMexicoAbout $48,000Roughly R$273,000Same combined average, not a pure data science bandArgentinaAbout $42,000Roughly R$239,000Same combined average; exchange rates move the peso valueChile, Colombia, PeruNo published average in this reportAsk the recruiter for the bandNo verified figure in this sourceUnited States reference$120,230 medianAbout $57.80 an hourData scientists only, May 2025, not a LATAM local salary
Match the row to who signs the paycheck. A product company in São Paulo prices against the Brazil anchor. A U.S. or European team hiring someone who lives in Lima is benchmarking a different market, even when both postings say data scientist. If your payer is abroad, don't stop at the local row.
How Seniority and US Benchmarks Set Your Range
One country average hides level. The public shape of U.S. data scientist pay in May 2025 is a distribution, not a single offer. In the May 2025 occupational wage release, the 25th percentile was $85,660, the median was $120,230, and the 75th percentile was $158,880. The mean was $126,800, with an hourly mean of $60.96 against an hourly median of $57.80.
Higher-paid people pull that mean up. Quoting $126,800 on a recruiter call overstates a typical offer. Copy the shape, not the dollars, when you place yourself inside a Brazil, Mexico, or Argentina row.
Position in the distributionAnnual wageHow to read it25th percentile$85,660Narrower or earlier-career scope in the US marketMedian$120,230Typical US data scientist, not a LATAM local offerMean$126,800Pulled up by high earners; a poor typical-offer quote75th percentile$158,880Senior scope and scarce skills at higher-paying US employers
Where your scope sits on your own row
Dashboard work and supervised reporting sit at the bottom of the country row you already chose. Independent experiments, or a model you maintain, sit near the middle. Staff scope sits at the top: owning a business metric, mentoring, or running a production model for a revenue team.
Match in this order. Years in the work come first, then a model you have shipped, then domain depth in fintech, retail, or health, then English with stakeholders, then whether the payer is local or international. Candidates in Bogotá, Lima, Córdoba, or Recife get more from that positioning than from a single headline number.
Demand is leverage, not a promise
The Bureau of Labor Statistics outlook for data scientists put the May 2025 median at $120,230, or $57.80 an hour, more than twice the $50,980 median for all occupations. Employment is projected to grow 35% from 2025 to 2035, against 3% for all occupations, with about 24,800 openings a year. That scarcity is why pay stays high for people who turn statistical or machine-learning methods into business systems.
A remote data scientist who owns production models, experimentation, or data infrastructure can clear a local anchor. Location discount and junior pay are not the same thing.
That outlook doesn't promise every applicant in Lima or Córdoba the U.S. median. Don't ask a Recife employer for the U.S. 75th percentile. Don't accept a junior local band from a U.S. team if you already own production work.
What Raises Pay Beyond the Country Average
Start from the country figure, then ask what moves an offer off it. The payer comes first. A local product company in São Paulo, a bank in Mexico City, or a retailer in Santiago prices against the local market. A U.S. or European team hiring someone who lives in Medellín, Lima, or Córdoba prices against a discount on its own salary band. That gap between a local contract and a foreign payroll is often wider than the jump from mid-level to senior inside one city.
Read the posting before you read the title. A requisition labeled "data scientist" that lists only weekly dashboards is a different offer from one that names a model in production, and the company profiles on LatoJobs show how each employer describes the work before you apply.
Industry, specialty, and the language of the meeting
Industry is the next split. Fintech, marketplaces, and companies that tie models to revenue or risk tend to pay more cash than early-stage startups, which often swap salary for equity that may never convert. Treat that pattern as directional. The published figures stop at country level, so verify each band with the recruiter.
Specialty compounds the effect. Experimentation, machine learning in production, and the data infrastructure around models outpay dashboard reporting, because those skills attach directly to revenue or cost. Adjacent technical markets price the same way: the skills for top-paying Web3 jobs illustrate how a scarce specialty moves an offer more than a location label does.
English raises pay when stakeholders sit in the United States or Europe. A requisition run entirely in Spanish or Portuguese stays priced on the local row.
Where you live and what you earn can move independently. Living costs in Recife, Rosario, or Lima sit below those of a more expensive capital, while an international payer still sets the band. That spread between local expenses and a foreign salary is where the largest gains hide.
Before you counter, check four things:
- Payer: local employer or international team
- Industry: which sector funds the role
- Scope: a model ships to production, or the job stops at reporting
- Language: the working language of the weekly stakeholder meeting
Example Packages for Real LATAM Situations
These three packages are teaching examples. Every dollar that isn't the country anchor or the U.S. median frame is something to confirm with the recruiter, not a surveyed band.
Say you're a mid-level data scientist onsite at a product company in São Paulo. Cash sits near the Brazil anchor of about $67,000. Local benefits often include health cover and a 13th salary, with little or no equity. Confirm the 13th salary. It isn't in the compensation report.
A hybrid role at a Mexican company in Mexico City is a different package. Cash sits near the Mexico anchor of about $48,000. Some employers add a bonus around one month of pay, and the team is Spanish-first, so there's no U.S. remote premium. Ask whether that month is contractual. Don't invent it into the offer.
The third situation is remote work from Buenos Aires, Bogotá, or Lima for a U.S. team. There isn't a surveyed remote average to quote. A practical negotiation frame is about 50 to 70 percent of the $120,230 U.S. median, roughly $60,000 to $84,000 in cash. That sits above the Argentina anchor and well below onsite U.S. pay. Label it as a frame, not a market study.
For a closer look at how candidates walk through offer math on a call, this walkthrough is worth ten minutes before you counter.
What else changes take-home
Bonus or an equity grant, contractor versus employee status, and a gross-up for taxes and benefits the contractor must purchase all affect the actual number. So does a currency clause. Argentine inflation can reduce a peso offer before the first renewal. The same situation can occur from Monterrey or Santiago when the team is abroad. A Chilean or Colombian local employer remains closer to a local benchmark, and those two countries still have no verified average in the 2025 comparison.
SituationCash anchorAlso in the packageHow to read itSão Paulo onsite, local product companyAbout $67,000Health cover and a 13th salary to confirm; little or no equityLocal market onlyMexico City hybrid, Mexican companyAbout $48,000Possible bonus; Spanish-first stakeholdersDo not add a US remote premiumRemote from Buenos Aires, Bogotá or Lima for a US teamAbout $60,000 to $84,000 as a teaching frameBonus or equity, contractor gross-up, currency clauseNot a surveyed average; above the local anchor and below US onsite pay
Total base, bonus, equity, and benefits before you compare two offers. A higher base with no health cover and no bonus can lose to a lower base that is fully loaded.
How to Negotiate a Data Science Offer
Use this order on the next call. Each move has one job.
- Name the benchmark that matches the payer before you state a number. Use the Brazil, Mexico, or Argentina anchor for a local contract. Use a share of the $120,230 U.S. median for a U.S. or European team. Naming the wrong market hands the recruiter your ceiling.
- Ask for a range, not a single figure, and say which scope it assumes. A range for dashboard reporting isn't a range for a model you maintain.
- Split the offer into base, bonus, equity, benefits and, for contractors, the gross-up for taxes, equipment, and unpaid leave. If you're pricing your own time rather than a payroll seat, it helps to set freelance rates with confidence so those costs sit inside the rate.
- Trade scope for cash only when you'll own it. Production models, an experiment roadmap, or English-language stakeholder work can justify a higher band. Unpaid extra scope shouldn't.
- Ask whether the band is already disclosed, and compare it with other open listings that publish pay rather than with a headline mean. The job search guides are a practical place to line those published bands up before the call.
- Get currency, payment country, and a review date in writing. For Argentina, ask whether the figure is in USD or indexed. A peso number can slip before the first renewal.
- If the base can't move, negotiate the bonus target, a signing amount, a learning budget, or an earlier review at six months. Silence after the first number is fine. A counter that restates scope is stronger than a counter that only restates hope.
Silence after their first number isn't awkward. It's the moment you decide whether the scope they described matches the benchmark you named.
Don't reopen the conversation by repeating a dream number. Restate the work: who the model serves, which metric you own, and which language the weekly meeting uses. That gives the hiring manager something to take back to compensation, instead of a request with no scope attached.
Screen Offers Against These Pay Anchors
Decide the payer type before you apply, not after someone names a number.
Step 1. Identify whether the payer is local or international. Local means an employer in São Paulo, Mexico City, Buenos Aires, or another domestic company. International means a U.S. or European team hiring from Bogotá, Lima, Córdoba, or Recife.
Step 2. Write down the matching anchor. For a local role that's about $67,000 in Brazil, $48,000 in Mexico, or $42,000 in Argentina. For an international team, use the teaching frame under the U.S. median, not the local row as a ceiling.
Step 3. Drop listings that sit far below that anchor once seniority is allowed for. Prefer listings that already show pay, so the first call is about scope.
Step 4. Compare an onsite role with a remote one only after you total base, bonus, equity, and benefits. A remote base that looks higher can lose once you buy your own health cover.
On LatoJobs you can browse by category, including Software Engineering, Data Science & AI, Sales & Business Development, Marketing, Content & Growth, Product Management, and Design. Some listings show a disclosed salary before you apply, and the platform also lists fully remote positions open to any LATAM resident. Filter those Data Science and AI openings by country, including roles aimed at residents of Brazil and Argentina, and read current market notes on the blog instead of an old screenshot of a range.
If the payer is local, negotiate around that country's anchor. If the payer is international, don't let the local anchor become the ceiling.
LatoJobs lists Data Science and AI roles across Latin America, including fully remote openings for residents of the region, and some postings show the salary before you apply. Use those disclosed bands to compare a local contract with a U.S. or European package instead of guessing from a headline mean. Visit LatoJobs and screen the payer before you send the application.
