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.
