Data Scientist II

As a Data Scientist II at Klivvr, you’ll play a key role in developing, optimizing, and deploying data-driven solutions that power our products and drive business decisions. You’ll work closely with cross-functional teams including Product, Engineering, Marketing, and Risk to deliver actionable insights and predictive models that shape the future of fintech in the region.

What you'll do:

• Design and implement advanced statistical models and machine learning algorithms for customer segmentation, credit scoring, fraud detection, and more.
• Translate business problems into analytical solutions with measurable impact.
• Collaborate with data engineers to productionize and scale models using best-in-class tools and infrastructure.
• Analyze user behavior and transactional data to identify trends, patterns, and opportunities.
• Present insights and recommendations clearly to non-technical stakeholders.
• Continuously improve model performance and maintain model health post-deployment.
• Contribute to the development of internal data science frameworks, tooling, and best practices.

To succeed in this role, you'll need to have:

• 2+ years of hands-on experience in data science or applied machine learning roles.
• Strong proficiency in Python (NumPy, pandas, scikit-learn, etc.) and SQL.
• Solid understanding of statistics, probability, and machine learning algorithms.
• Experience working with large-scale datasets and cloud platforms.
• Comfortable with version control tools (Git) and collaborative development workflows.
• Strong communication skills and the ability to work cross-functionally.

Preferrable to have:
• Experience in fintech or consumer finance domains.
• Familiarity with MLOps tools (e.g., MLflow, Airflow, Docker).
• Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with BI tools like Looker, Tableau, or Power BI.