Senior Data Scientist

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.

We are seeking a Senior Data Scientist to be one of the first data science hires for our newly formed ML team. This is a unique ground-floor opportunity to build our data science capabilities from scratch and have direct influence on our analytical and modeling approaches. This role combines advanced data science expertise with foundational contributions, requiring someone who can develop sophisticated models, conduct deep analytical research, and help establish the data science methodologies that will guide the team as we scale. As one of our founding data scientists, you'll work closely with our Tech Lead to shape our modeling approaches, define our analytical standards, and build the fundamental data science skill set for future hires.

What You'll Do

• Build foundational data science capabilities: As one of our first data science hires, work with the Tech Lead to develop core modeling methodologies, analytical frameworks, and research practices
• End-to-end model development: Take ownership of complete ML model lifecycle - from initial research and experimentation through production deployment and monitoring
• Build impactful models: Design, develop, and deploy machine learning models that solve complex business problems across payments, risk, and customer analytics
• Define analytical standards: Help establish best practices for data exploration, feature engineering, model validation, and statistical analysis
• Conduct deep research: Lead exploratory data analysis and research initiatives to uncover insights and identify ML opportunities across the business
• Partner with stakeholders: Work closely with business teams to understand requirements, translate problems into data science solutions, and communicate findings effectively
• Establish model development practices: Help set up our approach to model experimentation, A/B testing, and performance monitoring
• Shape data science culture: Contribute to establishing the team's analytical rigor, documentation standards, and knowledge-sharing practices
• Drive innovation: Research and evaluate new ML techniques, algorithms, and approaches that could benefit our business use cases
  
  

• 5+ years of experience in Machine Learning, Data Science, or related technical roles
• Excited about building something new and comfortable with the ambiguity of a startup-like environment within a larger company
• Proven track record of building and deploying machine learning models in production environments
• Strong proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn) and programming languages (Python, SQL)
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools and practices
• Excellent communication skills with ability to explain technical concepts to stakeholders and influence technical decisions
• Comfortable taking ownership, making decisions, and driving initiatives independently
• Bachelor's or Master's degree in Computer Science, AI, Data Science, Mathematics, or related quantitative field
• Experience in fintech or financial services is a plus