Time since we first saw it
Day 9
Similar jobs usually come down between day 4 and day 77.
At EBANX, jobs usually come down by about day 44.
From 51 similar postings that came down, and 13 of EBANX’s. Coming down is not always a hire.
Data Science Specialist
Curitiba | On-site
Live, first seen by us 9 days ago- Pay
- Pay not listed
- Work setting
On-site — work setting source
Listed location: Curitiba | On-site
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingDesign, build, evaluate and deploy ML and AI solutions at scale
Build models for fraud prevention, chargeback risk and credit card payment risk
Build and maintain production APIs, data pipelines and services for AI applications
Implement and oversee CI/CD pipelines for model deployment and updates
Troubleshoot production AI and ML issues and mentor team members
From the employer’s posting
Own the end-to-end design, development, evaluation, and deployment of Machine Learning and AI solutions
Build models and strategies focused on fraud prevention, chargeback risk, and risk prevention in credit card payments
Build and maintain production-grade solutions for AI applications, including APIs, data pipelines, and services
Implement and oversee continuous integration and continuous delivery (CI/CD) pipelines for AI model deployment and updates
Troubleshoot production issues related to AI and Machine Learning systems
Education & alternatives
- Experience collaborating closely with MLOps and AI Engineering teams; - Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field; EBANX offers:
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Nov 4, 20269 days ago
- Recorded sightings
- 9
- Last seen by us
- Nov 12, 2026
- Reposted
- once since Sep 20, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
EBANX is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Takes jobs down at a usual pace
- 50% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Azure
- Datadog
- Docker
- GCP
- XGBoost
Where the posting names them
- Proven expertise in developing and evaluating Machine Learning models, especially using XGBoost, Random Forest, and Decision Trees; - Strong programming skills in Python, with demonstrated experience in developing high-quality, maintainable code; - Experience working with Machine Learning models in real-world or production environments;
- Strong analytical and problem-solving skills, with the ability to translate business challenges into Machine Learning solutions; - Proficiency with cloud platforms (AWS, GCP or Azure), including deploying AI services and managing cloud resources; - Strong knowledge of CI/CD tools and processes (GitHub Actions);
- Solid understanding of data engineering concepts, ETL processes, and data pipeline architectures; - Experience with monitoring and logging solutions for ML systems (e.g., CloudWatch or DataDog); - Awareness of security standards and compliance requirements relevant to AI and data-driven systems;
- Experience developing or working with neural networks and other Machine Learning techniques; - Experience with containerization tools (Docker); - Experience collaborating closely with MLOps and AI Engineering teams;
- Own the end-to-end design, development, evaluation, and deployment of Machine Learning and AI solutions, ensuring scalability, reliability, and performance; - Develop and optimize Machine Learning models, with a strong focus on classical Machine Learning techniques such as XGBoost, Random Forest, and Decision Trees, ensuring robustness, explainability, and efficiency; - Build models and strategies focused on fraud prevention, chargeback risk, and risk prevention in credit card payments;
- Hands-on experience in Data Science and Machine Learning modeling; - Proven expertise in developing and evaluating Machine Learning models, especially using XGBoost, Random Forest, and Decision Trees; - Strong programming skills in Python, with demonstrated experience in developing high-quality, maintainable code;
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
Has EBANX posted this job before?
Yes. We’ve followed one other Data Science Specialist job there since April 2026. It came down after 6 days.
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
EBANX is one of the most successful fintechs to emerge from Latin America — and today, we are building a truly global payments company. Our mission has remained constant from day one: to unlock access and enable companies and consumers to participate in the digital economy, no matter where they are.
What started as a bold vision has grown into a platform that connects some of the world’s largest digital businesses with customers across 21 of the fastest-growing markets. We operate where complexity exists — turning local challenges into global opportunities, and building the infrastructure that allows payments to move further, faster, and smarter.
We are a team of builders and problem-solvers. We think globally, act with curiosity, and believe diversity of thought is a competitive advantage.
As EBANX enters its next phase of hyper growth, we are looking for people who want to shape the future of payments, expand what’s possible, and help connect businesses and consumers across borders.
Let’s build what’s next — together.
At EBANX’s Data team you don’t just work with numbers. You transform information into intelligence that drives strategic decisions and directly impacts the digital payments revolution on a global scale. Every analysis combines curiosity, rigor, and collaboration, making our work truly Out of the Ordinary.
• As an AI Engineer Specialist your mission will be to own the design and deployment of scalable AI systems in production.
Your day-to-day impact:
- Own the end-to-end design, development, evaluation, and deployment of Machine Learning and AI solutions, ensuring scalability, reliability, and performance;
- Develop and optimize Machine Learning models, with a strong focus on classical Machine Learning techniques such as XGBoost, Random Forest, and Decision Trees, ensuring robustness, explainability, and efficiency;
- Build models and strategies focused on fraud prevention, chargeback risk, and risk prevention in credit card payments;
- Translate business and payment-related challenges into effective Machine Learning solutions, considering both technical performance and business impact;
- Build and maintain production-grade solutions for AI applications, including APIs, data pipelines, and services, in collaboration with AI Engineering and MLOps specialists;
- Implement and oversee continuous integration and continuous delivery (CI/CD) pipelines for AI model deployment and updates;
- Collaborate closely with data scientists, AI engineers, MLOps specialists, software engineers, and stakeholders across teams to translate business requirements into actionable AI solutions;
- Troubleshoot production issues related to AI and Machine Learning systems, performing rigorous testing, validation, and continuous improvement;
- Contribute to the evolution of AI-powered solutions and explore new ways of applying AI to improve development efficiency and business outcomes;
- Mentor team members on best practices in Machine Learning modeling, AI engineering, model deployment, and system integration.
Must-haves to shine in this role:
- Hands-on experience in Data Science and Machine Learning modeling;
- Proven expertise in developing and evaluating Machine Learning models, especially using XGBoost, Random Forest, and Decision Trees;
- Strong programming skills in Python, with demonstrated experience in developing high-quality, maintainable code;
- Experience working with Machine Learning models in real-world or production environments;
- Strong analytical and problem-solving skills, with the ability to translate business challenges into Machine Learning solutions;
- Proficiency with cloud platforms (AWS, GCP or Azure), including deploying AI services and managing cloud resources;
- Strong knowledge of CI/CD tools and processes (GitHub Actions);
- Solid understanding of data engineering concepts, ETL processes, and data pipeline architectures;
- Experience with monitoring and logging solutions for ML systems (e.g., CloudWatch or DataDog);
- Awareness of security standards and compliance requirements relevant to AI and data-driven systems;
- Conversational English proficiency, with the ability to communicate effectively with international stakeholders.
Bonus points if you have:
- Prior experience in fraud prevention, fraud detection, chargeback, payment risk, financial services, fintech, or related industries;
- Experience developing or working with neural networks and other Machine Learning techniques;
- Experience with containerization tools (Docker);
- Experience collaborating closely with MLOps and AI Engineering teams;
- Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field;
EBANX offers:
- Performance Bonus: Annual bonus program based on company results.
- Meal Allowance: Monthly allowance to support your meals.
- EBANX Education: Financial assistance for undergraduate, graduate, and MBA programs to support your professional growth.
- EBANX Skills: Dedicated budget for courses, certifications, and workshops to encourage continuous learning.
- Language Classes: Language classes to support your personal and professional development.
- Health & Well-being: Medical and dental plans with extensive coverage, including support for dependents and wellness programs.
Flexible Work Culture: Semi-flexible hours, additional day off on your birthday, and year-end break to support work-life balance. - Well-being Program: Access to activities and resources that promote physical and mental health.
Learn more about our #ebanxlife on LinkedIn and Instagram, and see what it’s like to be part of a global team that breaks barriers, creates opportunities, and celebrates every achievement together.
✨ An Out Of The Ordinary career is waiting for you here!
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- Pay
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- Location & working pattern
Curitiba | On-site
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- Work authorization
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