As a
Data Scientist I 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 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:
- 1+ years of hands-on experience in data science or applied machine learning roles
- 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
Nice to have:
- Experience in fintech or consumer finance domains
- Familiarity with MLOps tools and practices (e.g., MLflow, Airflow, Docker)
- Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch)
