Data Scientist
Posted 6 Oct 2026
Advertised as “Senior Data Scientist”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- People management
- Employment
- Hybrid
- Contract
- Full-time
No salary listed for this role.
About Payoneer
Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.
By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.
Senior Data Scientist – AI & ML
Hybrid
Full-time
Role Summary
You’ll be one of the founding data scientists on our brand-new ML team, building Payoneer’s AI and data science capabilities from the ground up. Working closely with the Tech Lead, you’ll develop and deploy models across payments, risk and customer analytics, and build the frameworks that evaluate our GenAI and LLM-based agents. You’ll set the modeling standards, technical practices and culture the team will scale on, and help hire the data scientists who come next. It’s a great fit if you’re excited to build something new and own it end to end.
What You’ll Do
- Build evaluation frameworks for GenAI and LLM agents – golden datasets, LLM-as-judge, and quality, safety and compliance monitoring
- Own the full ML model lifecycle, from research and experimentation through production deployment and monitoring
- Design and deploy ML models that solve complex business problems across payments, risk and customer analytics
- Work with the Tech Lead to define core modeling methodologies, analytical standards and research practices
- Set up the team’s approach to feature engineering, model validation, experimentation, A/B testing and performance monitoring
- Lead exploratory research to uncover insights, identify ML opportunities and evaluate new techniques
- Partner with business stakeholders to translate problems into data science solutions and communicate findings clearly
- Shape the team’s culture and documentation standards, and help interview, onboard and mentor new data scientists
Who You Are
- 5+ years of experience in Machine Learning, Data Science or a related technical role
- Proven track record of building and deploying ML models in production environments
- GenAI/LLM evaluation experience – benchmark datasets, LLM-as-judge or human-in-the-loop evaluation, and monitoring of RAG and agent systems