Data Scientist
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Before you apply
SalaryNo pay range posted
LocationSan Francisco
Work modehybrid
Typefull-time
SeniorityLead
Experience5+ yrs
DepartmentTechnology
EquityIncluded
Company size51–200 people
PostedNov 2, 2026 · 6d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
5+ years of experience applying machine learning to real production problems, ideally in payments, fintech, fraud, or other high-volume transactional environments
Think like a research scientist: start from a problem, decide what data you need, choose the right modeling approach, and define how you will prove it works
Hands-on depth in feature generation, model selection, training, and hyperparameter optimization
Designed and run experiments, including A/B testing and experimentation platforms
Proficient in Python and SQL and comfortable querying large datasets in tools like Snowflake
Familiarity with tools such as TensorFlow and Airflow is expected
Self-directed; pushes for information needed and does not need close supervision
Communicates clearly with technical and non-technical audiences
Experience in guiding technical infrastructure teams to implement features that enable efficient data science and ML training pipelines
Own the end-to-end modeling lifecycle for payment optimization use cases
Build the experimentation framework to measure model performance
Partner with data teams to define and track building of data processing pipelines
Skills
Python
SQL
Snowflake
TensorFlow
Airflow
Benefits
Unlimited PTO
Remote work
Stock options
Internet support
Phone support
About the company
About DEUNA 🧡
We are a rapidly growing startup that simplifies global payments and powers next generation commerce in a single platform. With our products we’ve consolidated hundreds of payment solutions in a single integration, harness an intuitive payment orchestration method and centralize payment reconciliation.
We are currently present all across LATAM and looking for exceptional talent to join our team and continue revolutionizing the world of payments! 🚀
Visit https://www.deuna.com/ to learn more about us!
About the Role
We are looking for a hands-on data science leader to own machine learning and experimentation for DEUNA’s payments platform. You will be building the foundations of the data science practice at Deuna, working independently to design, train, and validate models that increase conversion, reduce declines, and reduce fraud in real-time payment flows across merchants and payment providers. You will be a part of the technology organization and will collaborate with project leads who own AI and modeling solutions for our customers, alongside existing data engineering and BI teams who already manage our data foundations and inference services. As DEUNA’s AI efforts grow, so will the team, and this role is a technical leadership role, with potential for people leadership if the skills align.
Who You Are
•
You have 5+ years of experience applying machine learning to real production problems, ideally in payments, fintech, fraud, or other high-volume transactional environments.
•
You think like a research scientist: you start from a problem, decide what data you need, choose the right modeling approach, and define how you will prove it works.
•
You have hands-on depth in feature generation, model selection, training, and hyperparameter optimization, and you know when a simple model beats a complex one.
•
You have designed and run experiments, including A/B testing and experimentation platforms, and can explain how you validated that a model delivered impact.
•
You are proficient in Python and SQL and comfortable querying large datasets in tools like Snowflake. Familiarity with tools such as TensorFlow and Airflow is expected, and you can explain how you have managed and rolled out models.
•
You are self-directed. You push for the information you need, and you do not need close supervision to keep work moving.
•
You communicate clearly with technical and non-technical audiences, including setting realistic expectations with leadership about what models can and cannot achieve.
•
You have experience in guiding technical infrastructure teams to implement features that enable efficient data science and ML training pipelines and systems
What You’ll Do
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Own the end-to-end modeling lifecycle for DEUNA’s payment optimization use cases: analyze merchant and transaction data, define modeling strategy, generate features, train and tune models, and release them through our existing inference infrastructure.
•
Build the experimentation framework we need to measure model performance while collaborating with system and infra engineers, from early signals through month-over-month results, and tie that performance to commitments on our merchant contracts and product pipeline.
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Partner with data teams to define and track building of data processing pipelines that surface insights that shape what DEUNA delivers. You will use experiments and rapid model iteration to tailor approaches to merchant data and goals, and work with the existing models while building new ones.
What will you find when you join DEUNA?
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A multicultural team distributed throughout LATAM
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Dynamism, agility and constant innovation
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Being part of a high-impact solution for an entire region
Benefits
•
The best tools and technology to operate
•
Being part of the startup culture.
•
We are in full expansion!
Benefits:
Vacations and additional PTO 🏝️
Remote work from anywhere 💻
Economic support for internet and cell phone line📱🌐
We all own DEUNA, we offer stock options 💸
Multidisciplinary, diverse and dynamic team 🧡
Growth and career path 🚀
Be part of a dynamic team that’s creating the next generation payments platform.
Join us at DEUNA!
Legal
DEUNA is proud to be an equal opportunity employer. We value and celebrate diversity and inclusion in our workplace. All employment decisions at DEUNA are made without discrimination based on nationality, race, ethnicity, religion, gender, sexual orientation, gender identity or expression, marital status, color, disability, or any other characteristic protected by law.