The fintech companies with the most data science and machine learning vacancies right now are Stripe, Coinbase, Checkout.com, Affirm and Adyen. As of 20 October 2026, Finjobsly tracked 360 live data, analytics and machine learning roles across 33 of the 36 employers on its panel, about 8.6% of the 4,185 active roles it follows. Stripe alone accounts for 44 of them and Coinbase for 35. The roles skew senior and remote, and the most requested skills are SQL and Python. This guide shows who is hiring, which role types they are filling, what they pay where pay is disclosed, and how to read the numbers.
Key findings
- Finjobsly tracked 360 live data and machine learning roles at 33 employers as of 20 October 2026, out of 4,185 active roles across 36 employers.
- The five largest employers by data role count are Stripe (44), Coinbase (35), Checkout.com (31), Affirm (30) and Adyen (22). Stripe and Coinbase together hold 79 of the 360 roles, so the market is concentrated.
- Senior is the most common level: 158 of the 360 roles are tagged Senior, 39 Staff and 24 Lead, against 87 Mid-Level, 15 internships and 35 Junior.
- Of the 274 roles with a work style tagged, 197 are remote (72%), 64 hybrid and 13 onsite.
- SQL appears in the skill tags of 207 of the 360 roles and Python in 196. Machine Learning appears in 112, Payments in 150 and Fraud in 102.
- Among USD-paid roles that disclose a range, median advertised pay is highest for machine learning roles (a median range of $223,493 to $295,900, n=24) and lowest for risk and fraud analytics ($135,320 to $170,000, n=11).
Which fintech companies are hiring the most data scientists?
Hiring volume is a measurable signal, not a quality ranking. The table counts live roles on Finjobsly whose titles match data science, machine learning, data or analytics engineering, data or business analytics, or risk and fraud modelling, as of 20 October 2026. It covers Finjobsly's panel of 36 tracked employers, not every fintech.
| Employer | Data and ML roles | Data scientist | Machine learning | Data and analytics engineer | Analyst | Risk and fraud analytics |
|---|---|---|---|---|---|---|
| Stripe | 44 | 8 | 11 | 1 | 16 | 8 |
| Coinbase | 35 | 4 | 9 | 4 | 11 | 7 |
| Checkout.com | 31 | 5 | 2 | 0 | 18 | 6 |
| Affirm | 30 | 0 | 9 | 4 | 13 | 4 |
| Adyen | 22 | 0 | 6 | 4 | 2 | 10 |
| Monzo | 18 | 6 | 6 | 1 | 5 | 0 |
| Plaid | 17 | 5 | 5 | 2 | 1 | 4 |
| Block | 15 | 3 | 2 | 4 | 6 | 0 |
| Tide | 14 | 0 | 0 | 0 | 7 | 7 |
| Nubank | 13 | 0 | 5 | 0 | 8 | 0 |
| GoCardless | 11 | 6 | 0 | 2 | 3 | 0 |
| Brex | 9 | 0 | 2 | 2 | 5 | 0 |
| Robinhood | 9 | 3 | 2 | 1 | 3 | 0 |
Chime and Ramp each had 8 roles, Gusto, Mercury, Qonto and Zopa 7 each, SoFi 6, and a further 13 employers had five or fewer. Stripe's 44 roles are 12% of all data roles in the panel, which means any "share of the market" figure in this article is partly a statement about Stripe. Rows are counted by title, so a role can only sit in one column.
Three patterns stand out. Monzo (12 of 18 roles) and Plaid (10 of 17) lean towards data scientist and machine learning titles. Checkout.com's data hiring is mostly analyst roles (18 of 31), and Adyen's is mostly risk and fraud analytics (10 of 22). You can browse every live role through the fintech jobs page and the fintech company directory.
What types of data jobs are fintech companies recruiting for?
Finjobsly's 360 roles split across five families, based on job titles:
- Data and business analysts: 146 roles at 31 employers. This is the broadest family and the most common entry point, and 38 of these roles disclose a USD range.
- Data scientists: 52 roles at 16 employers, including product, fraud, lending and risk-focused scientists.
- Machine learning engineers and scientists: 71 roles at 17 employers, covering fraud models, ML platforms, identity and customer experience.
- Risk and fraud analytics: 56 roles at 14 employers, including credit model risk and financial crime analytics.
- Data and analytics engineers: 35 roles at 19 employers, building the pipelines and market data that the other teams rely on.
Because the families are assigned by title keywords, borderline titles such as "software engineer, ML platform" are classed with machine learning and some product analyst roles may sit in the analyst family. Treat the splits as a guide, not an official taxonomy.
What seniority level are fintech data science jobs?
Senior and above dominates. Of the 360 roles, 158 are tagged Senior, 39 Staff and 24 Lead (221 in total), against 87 Mid-Level, 15 internships and 35 Junior roles. Two roles had no level tagged. Candidates earlier in their careers will find far fewer openings. If you are a junior candidate, the fintech data analyst salary guide is a better starting point than a data scientist search.
Are fintech data science jobs remote?
Mostly, among those that state it. Work style is tagged on 274 of the 360 roles: 197 are remote (71.9%), 64 hybrid (23.4%) and 13 onsite (4.7%). The other 86 roles have no work style recorded, so the true remote share may be different. Note that "remote" in a job posting often still carries a country or time zone restriction, so check the posting.
What skills do fintech data science jobs ask for?
These counts come from the skills tags on the same 360 roles, as of 20 October 2026. A role can carry several tags.
- SQL: 207 roles (58%)
- Python: 196 roles (54%)
- Payments: 150 roles
- Machine Learning: 112 roles
- Data Science: 111 roles
- Compliance: 108 roles
- Fraud: 102 roles
- Risk Management: 51 roles
- Go: 50 roles
- REST: 50 roles
- Data Engineering: 45 roles
- AML: 45 roles
The domain tags matter as much as the tools. Payments (150), Compliance (108) and Fraud (102) show up on a large share of data roles, which supports a point many hiring managers make: knowing how money moves and which controls apply is part of the job. SQL and Python are the most common tags, each on more than half of roles, so they are the baseline rather than a differentiator. Because Stripe and Coinbase supply about a fifth of the roles, some of these tags reflect their stacks and products.
How much do fintech data scientists earn?
Finjobsly's figures use only roles that advertise a salary range in US dollars. 154 of the 360 roles disclose some pay, and 98 of them are USD-denominated with both a minimum and a maximum (we excluded any with a minimum under $40,000). The table shows the median of the advertised minimum and the median of the advertised maximum for each family. Sample sizes are small, and anything under 20 should be read as indicative.
| Role family | Median advertised minimum (USD) | Median advertised maximum (USD) | Roles (n) |
|---|---|---|---|
| Machine learning | $223,493 | $295,900 | 24 |
| Data scientist | $180,370 | $230,000 | 15 |
| Data and analytics engineer | $168,300 | $222,900 | 10 |
| Data and business analyst | $135,320 | $179,350 | 38 |
| Risk and fraud analytics | $135,320 | $170,000 | 11 |
These are advertised ranges at the employers in Finjobsly's panel, concentrated in US tech-led fintechs where pay disclosure is common or legally required. They are not market averages and they exclude roles paid in other currencies. For context, the US Bureau of Labor Statistics reports a median annual wage of $120,230 for data scientists across all industries as of May 2025 and projects employment growth of 35% from 2025 to 2035 (US Bureau of Labor Statistics, Occupational Outlook Handbook, accessed 1 October 2026). Advertised fintech ranges at the senior end sit well above that all-industry median. To check a specific offer, use the Finjobsly Salary Benchmark.
Which fintech companies are worth considering for a data science career?
There is not enough comparable evidence, such as retention, promotion or model-quality data, to rank employers numerically, so this is a shortlist based on observable hiring signals rather than a league table.
- Breadth of data roles: Stripe, Coinbase and Plaid are hiring in all five families, which suggests larger and more specialised data organisations.
- Machine learning and data science depth: Monzo (12 of 18 roles are data scientist or machine learning titles) and Plaid (10 of 17) concentrate on modelling.
- Risk and fraud specialisation: Adyen lists 10 risk and fraud analytics roles among its 22, Stripe 8 and Coinbase 7.
- Disclosed pay: Affirm (89% of its live roles), Chime (88%) and Coinbase (87%) post a salary range on most roles, which makes their roles easier to compare.
Hiring volume says nothing about culture or management quality. Read the individual job posts and company pages before applying.
Current opportunities
Browse live roles on the fintech jobs page or in the company directory. For a view of how this fits the wider market, read which fintechs are hiring for AI roles and the Finjobsly Fintech Hiring Index.
Methodology
All Finjobsly figures come from the platform's live job database, as of 20 October 2026, covering 4,185 active roles across 36 tracked employers. This panel is not the whole fintech market, so the figures describe roles Finjobsly tracks. A role counts as data, analytics or machine learning if its title matches data scientist, machine learning, ML, MLOps, applied or research scientist, data engineer, analytics engineer, data analyst, business intelligence, analytics, or a fraud, risk or credit analytics or modelling title. Sales, marketing, product, program, partnerships, solutions, customer success, recruiting, legal and accounting titles are excluded. The matching was re-run for this update and the panel has grown since 1 October, so the 360 roles here should not be compared with the 186 reported in the earlier edition. Skills counts use each role's skill tags. Work style, seniority and pay are shown only where recorded. Work style is missing on 86 roles. Country data is not consistently recorded, so this article does not report location splits. Salary figures cover USD-paid roles only, and per-family sample sizes are small. External figures are from the US Bureau of Labor Statistics.
Last updated: 20 October 2026.
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